---
base_model: microsoft/mpnet-base
datasets:
- sentence-transformers/natural-questions
language:
- en
library_name: sentence-transformers
license: apache-2.0
metrics:
- cosine_accuracy@1
- cosine_accuracy@3
- cosine_accuracy@5
- cosine_accuracy@10
- cosine_precision@1
- cosine_precision@3
- cosine_precision@5
- cosine_precision@10
- cosine_recall@1
- cosine_recall@3
- cosine_recall@5
- cosine_recall@10
- cosine_ndcg@10
- cosine_mrr@10
- cosine_map@100
- dot_accuracy@1
- dot_accuracy@3
- dot_accuracy@5
- dot_accuracy@10
- dot_precision@1
- dot_precision@3
- dot_precision@5
- dot_precision@10
- dot_recall@1
- dot_recall@3
- dot_recall@5
- dot_recall@10
- dot_ndcg@10
- dot_mrr@10
- dot_map@100
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:100231
- loss:ImprovedContrastiveLoss
widget:
- source_sentence: when did the british leave new york city
sentences:
- Golden State Warriors The Golden State Warriors are an American professional basketball
team based in Oakland, California. The Warriors compete in the National Basketball
Association (NBA) as a member of the league's Western Conference Pacific Division.
The Warriors play their home games at the Oracle Arena in Oakland. The Warriors
have reached nine NBA Finals, winning five NBA championships in 1947,[b] 1956,
1975, 2015 and 2017. Golden State's five NBA championships are tied for fourth-most
in NBA history with the San Antonio Spurs, and behind only the Boston Celtics
(17), Los Angeles Lakers (16) and Chicago Bulls (6). As of 2017, the Warriors
are the third most valuable NBA franchise according to Forbes, with an estimated
value of $2.6Â billion.[6]
- Evacuation Day (New York) Evacuation Day on November 25 marks the day in 1783
when British troops departed from New York City on Manhattan Island, after the
end of the American Revolutionary War. After this British Army evacuation, General
George Washington triumphantly led the Continental Army from his former headquarters,
north of the city, across the Harlem River south down Manhattan through the town
to The Battery at the foot of Broadway.[1]
- Biochemical oxygen demand BOD can be used as a gauge of the effectiveness of wastewater
treatment plants. It is listed as a conventional pollutant in the U.S. Clean Water
Act.[2]
- source_sentence: what is the newest generation of the ipad
sentences:
- Alex Karev Alex is fired by Dr. Lebackes when Maggie Pierce accidentally reveals
to him that Karev was thinking about leaving the job. Webber recommended Bailey
to fill Yang's board seat after she left, so Bailey and Alex fight over the chair.
They both make presentations to the board and eventually Bailey wins, with a unanimous
vote in her favor. He is hired back as an attending Peds surgeon and takes over
full-time as Arizona pursues a fellowship with Dr. Herman. Alex continues to date
Jo and his friendship with Meredith grows stronger than ever, with him taking
on the role of her new person. When Derek dies and Meredith runs away, Alex is
upset by her leaving without telling him where she went and calls her everyday.
Eventually she calls him, tells him she is okay, and to stop calling. When she
goes into labor and gives birth to Ellis Shepherd, Alex goes to see her since
he is her emergency contact. He brings Meredith and her kids back to her house.
She asks to move back in with him in her old house. Alex sells Meredith back the
house and he and Jo rent a loft.
- List of presidents of the United States by age The median age upon accession to
the presidency is 55 years and 3 months. This is how old Lyndon B. Johnson was
at the time of his inauguration. The youngest person to assume the office was
Theodore Roosevelt, who became president at the age of 42 years, 322 days, following
William McKinley's assassination; the oldest was Donald Trump, who was 70 years,
220 days old at his inauguration. The youngest person to be elected president
was John F. Kennedy, at 43 years, 163 days of age on election day; the oldest
was Ronald Reagan, who was 73 years, 274 days old at the time of his election
to a second term.
- iPad (2018) The iPad (officially sixth-generation iPad) is a 9.7-inch (25cm) tablet
computer designed, developed, and marketed by Apple Inc. It was announced on March
27, 2018 during an education-focused event in Chicago and it is a revision of
the 2017 model, upgraded with the Apple A10 Fusion SoC and support for styluses
such as Apple Pencil.[2] The iPad is marketed towards educators and schools.
- source_sentence: what is the average speed of passenger airplane
sentences:
- Fixed exchange-rate system In the 21st century, the currencies associated with
large economies typically do not fix or peg exchange rates to other currencies.
The last large economy to use a fixed exchange rate system was the People's Republic
of China which, in July 2005, adopted a slightly more flexible exchange rate system
called a managed exchange rate.[2] The European Exchange Rate Mechanism is also
used on a temporary basis to establish a final conversion rate against the Euro
(€) from the local currencies of countries joining the Eurozone.
- Tenth Doctor The Tenth Doctor is an incarnation of the Doctor, the protagonist
of the BBC science fiction television programme Doctor Who, who is played by David
Tennant in three series as well as nine specials. As with previous incarnations
of the Doctor, the character has also appeared in other Doctor Who spin-offs.
In the programme's narrative, the Doctor is a centuries-old Time Lord alien from
the planet Gallifrey who travels in time in his TARDIS, frequently with companions.
When the Doctor is critically injured beyond medical repair, he can regenerate
his body; in doing so, his physical appearance and personality change, and a new
actor assumes the role. Tennant's portrayal of the Doctor is of an outwardly charismatic
and charming adventurer whose likable and easygoing attitude can quickly turn
to righteous fury when provoked.
- Cruise (aeronautics) The typical cruising airspeed for a long-distance commercial
passenger aircraft is approximately 475–500 knots (878–926 km/h; 546–575 mph).
- source_sentence: when is cars three going to be released
sentences:
- Benedict's reagent The color of the obtained precipitate gives an idea about the
quantity of sugar present in the solution, hence the test is semi-quantitative.
A greenish precipitate indicates about 0.5 g% concentration; yellow precipitate
indicates 1 g% concentration; orange indicates 1.5 g% and red indicates 2 g% or
higher concentration.
- Cars 3 The film was released on June 16, 2017, has grossed over $362 million worldwide
and received generally positive reviews, with many critics considering it an improvement
over its predecessor, as well as praising its emotional story and animation.[7]
- Sleeping Beauty At the christening of a king and queen's long-wished-for child,
seven good fairies are invited to be godmothers to the infant princess. The fairies
attend the banquet at the palace. Each fairy is presented with a golden plate
and drinking cups adorned with jewels. Soon after, an old fairy enters the palace
and is seated with a plate of fine china and a crystal drinking glass. This old
fairy is overlooked because she has been within a tower for many years and everyone
had believed her to be deceased. Six of the other seven fairies then offer their
gifts of beauty, wit, grace, dance, song, and goodness to the infant princess.
The evil fairy is very angry about having been forgotten, and as her gift, enchants
the infant princess so that she will one day prick her finger on a spindle of
a spinning wheel and die. The seventh fairy, who hasn't yet given her gift, attempts
to reverse the evil fairy's curse. However, she can only do so partially. Instead
of dying, the Princess will fall into a deep sleep for 100 years and be awakened
by a kiss from a king's son.
- source_sentence: who was ancient china's main enemy that lived to the north
sentences:
- Betty Lynn Elizabeth Ann Theresa "Betty" Lynn[1] (born August 29, 1926) is a former
American actress. She is best known for her role as Thelma Lou, Deputy Barney
Fife's girlfriend, on The Andy Griffith Show.
- Sampath Bank Sampath Bank PLC is a licensed commercial bank incorporated in Sri
Lanka in 1986 with 229 branches and 373 ATMs island wide. It has won the "Bank
of the Year" award by "The Banker" of Financial Times Limited – London, for
the second consecutive year and the "National Business Excellence Awards 2010".[citation
needed] It has become the third largest private sector bank in Sri Lanka with
Rs. 453 billion in deposits as of 30 June 2016.[1]
- 'Sui dynasty The Sui Dynasty (Chinese: 隋朝; pinyin: Suí cháo) was a short-lived
imperial dynasty of China of pivotal significance. The Sui unified the Northern
and Southern dynasties and reinstalled the rule of ethnic Han Chinese in the entirety
of China proper, along with sinicization of former nomadic ethnic minorities (the
Five Barbarians) within its territory. It was succeeded by the Tang dynasty, which
largely inherited its foundation.'
co2_eq_emissions:
emissions: 171.00505800984172
energy_consumed: 0.4399387140015789
source: codecarbon
training_type: fine-tuning
on_cloud: false
cpu_model: 13th Gen Intel(R) Core(TM) i7-13700K
ram_total_size: 31.777088165283203
hours_used: 1.139
hardware_used: 1 x NVIDIA GeForce RTX 3090
model-index:
- name: MPNet base trained on Natural Questions pairs
results:
- task:
type: information-retrieval
name: Information Retrieval
dataset:
name: natural questions dev
type: natural-questions-dev
metrics:
- type: cosine_accuracy@1
value: 0.5886032645880168
name: Cosine Accuracy@1
- type: cosine_accuracy@3
value: 0.8148763561724172
name: Cosine Accuracy@3
- type: cosine_accuracy@5
value: 0.8832958655067931
name: Cosine Accuracy@5
- type: cosine_accuracy@10
value: 0.9410614798162448
name: Cosine Accuracy@10
- type: cosine_precision@1
value: 0.5886032645880168
name: Cosine Precision@1
- type: cosine_precision@3
value: 0.27162545205747235
name: Cosine Precision@3
- type: cosine_precision@5
value: 0.17665917310135862
name: Cosine Precision@5
- type: cosine_precision@10
value: 0.09410614798162449
name: Cosine Precision@10
- type: cosine_recall@1
value: 0.5886032645880168
name: Cosine Recall@1
- type: cosine_recall@3
value: 0.8148763561724172
name: Cosine Recall@3
- type: cosine_recall@5
value: 0.8832958655067931
name: Cosine Recall@5
- type: cosine_recall@10
value: 0.9410614798162448
name: Cosine Recall@10
- type: cosine_ndcg@10
value: 0.769304304207993
name: Cosine Ndcg@10
- type: cosine_mrr@10
value: 0.7136417796519368
name: Cosine Mrr@10
- type: cosine_map@100
value: 0.7163262351468975
name: Cosine Map@100
- type: dot_accuracy@1
value: 0.5153943896002345
name: Dot Accuracy@1
- type: dot_accuracy@3
value: 0.7485094321180725
name: Dot Accuracy@3
- type: dot_accuracy@5
value: 0.8219137914182387
name: Dot Accuracy@5
- type: dot_accuracy@10
value: 0.8932655654383735
name: Dot Accuracy@10
- type: dot_precision@1
value: 0.5153943896002345
name: Dot Precision@1
- type: dot_precision@3
value: 0.2495031440393575
name: Dot Precision@3
- type: dot_precision@5
value: 0.16438275828364773
name: Dot Precision@5
- type: dot_precision@10
value: 0.08932655654383737
name: Dot Precision@10
- type: dot_recall@1
value: 0.5153943896002345
name: Dot Recall@1
- type: dot_recall@3
value: 0.7485094321180725
name: Dot Recall@3
- type: dot_recall@5
value: 0.8219137914182387
name: Dot Recall@5
- type: dot_recall@10
value: 0.8932655654383735
name: Dot Recall@10
- type: dot_ndcg@10
value: 0.7056782708639685
name: Dot Ndcg@10
- type: dot_mrr@10
value: 0.6453053511503243
name: Dot Mrr@10
- type: dot_map@100
value: 0.6498747716288641
name: Dot Map@100
---
# MPNet base trained on Natural Questions pairs
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [microsoft/mpnet-base](https://huggingface.co/microsoft/mpnet-base) on the [natural-questions](https://huggingface.co/datasets/sentence-transformers/natural-questions) dataset. It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
## Model Details
### Model Description
- **Model Type:** Sentence Transformer
- **Base model:** [microsoft/mpnet-base](https://huggingface.co/microsoft/mpnet-base)
- **Maximum Sequence Length:** 512 tokens
- **Output Dimensionality:** 768 tokens
- **Similarity Function:** Cosine Similarity
- **Training Dataset:**
- [natural-questions](https://huggingface.co/datasets/sentence-transformers/natural-questions)
- **Language:** en
- **License:** apache-2.0
### Model Sources
- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
### Full Model Architecture
```
SentenceTransformer(
(0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: MPNetModel
(1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
)
```
## Usage
### Direct Usage (Sentence Transformers)
First install the Sentence Transformers library:
```bash
pip install -U sentence-transformers
```
Then you can load this model and run inference.
```python
from sentence_transformers import SentenceTransformer
# Download from the 🤗 Hub
model = SentenceTransformer("tomaarsen/mpnet-base-natural-questions-icl")
# Run inference
sentences = [
"who was ancient china's main enemy that lived to the north",
'Sui dynasty The Sui Dynasty (Chinese: 隋朝; pinyin: Suí cháo) was a short-lived imperial dynasty of China of pivotal significance. The Sui unified the Northern and Southern dynasties and reinstalled the rule of ethnic Han Chinese in the entirety of China proper, along with sinicization of former nomadic ethnic minorities (the Five Barbarians) within its territory. It was succeeded by the Tang dynasty, which largely inherited its foundation.',
'Sampath Bank Sampath Bank PLC is a licensed commercial bank incorporated in Sri Lanka in 1986 with 229 branches and 373 ATMs island wide. It has won the "Bank of the Year" award by "The Banker" of Financial Times Limited – London, for the second consecutive year and the "National Business Excellence Awards 2010".[citation needed] It has become the third largest private sector bank in Sri Lanka with Rs. 453 billion in deposits as of 30 June 2016.[1]',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 768]
# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]
```
## Evaluation
### Metrics
#### Information Retrieval
* Dataset: `natural-questions-dev`
* Evaluated with [InformationRetrievalEvaluator](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator)
| Metric | Value |
|:--------------------|:-----------|
| cosine_accuracy@1 | 0.5886 |
| cosine_accuracy@3 | 0.8149 |
| cosine_accuracy@5 | 0.8833 |
| cosine_accuracy@10 | 0.9411 |
| cosine_precision@1 | 0.5886 |
| cosine_precision@3 | 0.2716 |
| cosine_precision@5 | 0.1767 |
| cosine_precision@10 | 0.0941 |
| cosine_recall@1 | 0.5886 |
| cosine_recall@3 | 0.8149 |
| cosine_recall@5 | 0.8833 |
| cosine_recall@10 | 0.9411 |
| cosine_ndcg@10 | 0.7693 |
| cosine_mrr@10 | 0.7136 |
| **cosine_map@100** | **0.7163** |
| dot_accuracy@1 | 0.5154 |
| dot_accuracy@3 | 0.7485 |
| dot_accuracy@5 | 0.8219 |
| dot_accuracy@10 | 0.8933 |
| dot_precision@1 | 0.5154 |
| dot_precision@3 | 0.2495 |
| dot_precision@5 | 0.1644 |
| dot_precision@10 | 0.0893 |
| dot_recall@1 | 0.5154 |
| dot_recall@3 | 0.7485 |
| dot_recall@5 | 0.8219 |
| dot_recall@10 | 0.8933 |
| dot_ndcg@10 | 0.7057 |
| dot_mrr@10 | 0.6453 |
| dot_map@100 | 0.6499 |
## Training Details
### Training Dataset
#### natural-questions
* Dataset: [natural-questions](https://huggingface.co/datasets/sentence-transformers/natural-questions) at [f9e894e](https://huggingface.co/datasets/sentence-transformers/natural-questions/tree/f9e894e1081e206e577b4eaa9ee6de2b06ae6f17)
* Size: 100,231 training samples
* Columns: query and answer
* Approximate statistics based on the first 1000 samples:
| | query | answer |
|:--------|:-----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|
| type | string | string |
| details | - min: 10 tokens
- mean: 11.74 tokens
- max: 21 tokens
| - min: 17 tokens
- mean: 135.66 tokens
- max: 512 tokens
|
* Samples:
| query | answer |
|:----------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| when did richmond last play in a preliminary final | Richmond Football Club Richmond began 2017 with 5 straight wins, a feat it had not achieved since 1995. A series of close losses hampered the Tigers throughout the middle of the season, including a 5-point loss to the Western Bulldogs, 2-point loss to Fremantle, and a 3-point loss to the Giants. Richmond ended the season strongly with convincing victories over Fremantle and St Kilda in the final two rounds, elevating the club to 3rd on the ladder. Richmond's first final of the season against the Cats at the MCG attracted a record qualifying final crowd of 95,028; the Tigers won by 51 points. Having advanced to the first preliminary finals for the first time since 2001, Richmond defeated Greater Western Sydney by 36 points in front of a crowd of 94,258 to progress to the Grand Final against Adelaide, their first Grand Final appearance since 1982. The attendance was 100,021, the largest crowd to a grand final since 1986. The Crows led at quarter time and led by as many as 13, but the Tigers took over the game as it progressed and scored seven straight goals at one point. They eventually would win by 48 points – 16.12 (108) to Adelaide's 8.12 (60) – to end their 37-year flag drought.[22] Dustin Martin also became the first player to win a Premiership medal, the Brownlow Medal and the Norm Smith Medal in the same season, while Damien Hardwick was named AFL Coaches Association Coach of the Year. Richmond's jump from 13th to premiers also marked the biggest jump from one AFL season to the next. |
| who sang what in the world's come over you | Jack Scott (singer) At the beginning of 1960, Scott again changed record labels, this time to Top Rank Records.[1] He then recorded four Billboard Hot 100 hits – "What in the World's Come Over You" (#5), "Burning Bridges" (#3) b/w "Oh Little One" (#34), and "It Only Happened Yesterday" (#38).[1] "What in the World's Come Over You" was Scott's second gold disc winner.[6] Scott continued to record and perform during the 1960s and 1970s.[1] His song "You're Just Gettin' Better" reached the country charts in 1974.[1] In May 1977, Scott recorded a Peel session for BBC Radio 1 disc jockey, John Peel. |
| who produces the most wool in the world | Wool Global wool production is about 2 million tonnes per year, of which 60% goes into apparel. Wool comprises ca 3% of the global textile market, but its value is higher owing to dying and other modifications of the material.[1] Australia is a leading producer of wool which is mostly from Merino sheep but has been eclipsed by China in terms of total weight.[30] New Zealand (2016) is the third-largest producer of wool, and the largest producer of crossbred wool. Breeds such as Lincoln, Romney, Drysdale, and Elliotdale produce coarser fibers, and wool from these sheep is usually used for making carpets. |
* Loss: __main__.ImprovedContrastiveLoss with these parameters:
```json
{
"temperature": 0.01
}
```
### Evaluation Dataset
#### natural-questions
* Dataset: [natural-questions](https://huggingface.co/datasets/sentence-transformers/natural-questions) at [f9e894e](https://huggingface.co/datasets/sentence-transformers/natural-questions/tree/f9e894e1081e206e577b4eaa9ee6de2b06ae6f17)
* Size: 100,231 evaluation samples
* Columns: query and answer
* Approximate statistics based on the first 1000 samples:
| | query | answer |
|:--------|:-----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|
| type | string | string |
| details | - min: 10 tokens
- mean: 11.79 tokens
- max: 25 tokens
| - min: 15 tokens
- mean: 142.78 tokens
- max: 512 tokens
|
* Samples:
| query | answer |
|:--------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| who betrayed siraj ud daula in the battle of plassey in 1757 | Siraj ud-Daulah The Battle of Plassey (or Palashi) is widely considered the turning point in the history of the subcontinent, and opened the way to eventual British domination. After Siraj-ud-Daulah's conquest of Calcutta, the British sent fresh troops from Madras to recapture the fort and avenge the attack. A retreating Siraj-ud-Daulah met the British at Plassey. He had to make camp 27 miles away from Murshidabad. On 23 June 1757 Siraj-ud-Daulah called on Mir Jafar because he was saddened by the sudden fall of Mir Mardan who was a very dear companion of Siraj in battles. The Nawab asked for help from Mir Jafar. Mir Jafar advised Siraj to retreat for that day. The Nawab made the blunder in giving the order to stop the fight. Following his command, the soldiers of the Nawab were returning to their camps. At that time, Robert Clive attacked the soldiers with his army. At such a sudden attack, the army of Siraj became indisciplined and could think of no way to fight. So all fled away in such a situation. Betrayed by a conspiracy plotted by Jagat Seth, Mir Jafar, Krishna Chandra, Omichund etc., he lost the battle and had to escape. He went first to Murshidabad and then to Patna by boat, but was eventually arrested by Mir Jafar's soldiers. |
| what is the meaning of single malt whisky | Single malt whisky Single malt whisky is malt whisky from a single distillery, that is, whisky distilled from fermented mash made exclusively with malted grain (usually barley), as distinguished from unmalted grain. |
| when is despicable me 3 going to release | Despicable Me 3 Despicable Me 3 premiered on June 14, 2017, at the Annecy International Animated Film Festival, and was released in the United States on June 30, 2017, by Universal Pictures in 3D, RealD 3D, Dolby Cinema, and IMAX 3D. The film received mixed reviews from critics[7] and has grossed over $1 billion worldwide, making it the third highest-grossing film of 2017, the fifth highest-grossing animated film of all time and the 28th highest-grossing overall. It is Illumination's second film to gross over $1 billion, after Minions in 2015, becoming the first ever animated franchise to do so. |
* Loss: __main__.ImprovedContrastiveLoss with these parameters:
```json
{
"temperature": 0.01
}
```
### Training Hyperparameters
#### Non-Default Hyperparameters
- `eval_strategy`: steps
- `per_device_train_batch_size`: 32
- `per_device_eval_batch_size`: 32
- `learning_rate`: 2e-05
- `num_train_epochs`: 1
- `warmup_ratio`: 0.1
- `bf16`: True
- `batch_sampler`: no_duplicates
#### All Hyperparameters
Click to expand
- `overwrite_output_dir`: False
- `do_predict`: False
- `eval_strategy`: steps
- `prediction_loss_only`: True
- `per_device_train_batch_size`: 32
- `per_device_eval_batch_size`: 32
- `per_gpu_train_batch_size`: None
- `per_gpu_eval_batch_size`: None
- `gradient_accumulation_steps`: 1
- `eval_accumulation_steps`: None
- `learning_rate`: 2e-05
- `weight_decay`: 0.0
- `adam_beta1`: 0.9
- `adam_beta2`: 0.999
- `adam_epsilon`: 1e-08
- `max_grad_norm`: 1.0
- `num_train_epochs`: 1
- `max_steps`: -1
- `lr_scheduler_type`: linear
- `lr_scheduler_kwargs`: {}
- `warmup_ratio`: 0.1
- `warmup_steps`: 0
- `log_level`: passive
- `log_level_replica`: warning
- `log_on_each_node`: True
- `logging_nan_inf_filter`: True
- `save_safetensors`: True
- `save_on_each_node`: False
- `save_only_model`: False
- `restore_callback_states_from_checkpoint`: False
- `no_cuda`: False
- `use_cpu`: False
- `use_mps_device`: False
- `seed`: 42
- `data_seed`: None
- `jit_mode_eval`: False
- `use_ipex`: False
- `bf16`: True
- `fp16`: False
- `fp16_opt_level`: O1
- `half_precision_backend`: auto
- `bf16_full_eval`: False
- `fp16_full_eval`: False
- `tf32`: None
- `local_rank`: 0
- `ddp_backend`: None
- `tpu_num_cores`: None
- `tpu_metrics_debug`: False
- `debug`: []
- `dataloader_drop_last`: False
- `dataloader_num_workers`: 0
- `dataloader_prefetch_factor`: None
- `past_index`: -1
- `disable_tqdm`: False
- `remove_unused_columns`: True
- `label_names`: None
- `load_best_model_at_end`: False
- `ignore_data_skip`: False
- `fsdp`: []
- `fsdp_min_num_params`: 0
- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
- `fsdp_transformer_layer_cls_to_wrap`: None
- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
- `deepspeed`: None
- `label_smoothing_factor`: 0.0
- `optim`: adamw_torch
- `optim_args`: None
- `adafactor`: False
- `group_by_length`: False
- `length_column_name`: length
- `ddp_find_unused_parameters`: None
- `ddp_bucket_cap_mb`: None
- `ddp_broadcast_buffers`: False
- `dataloader_pin_memory`: True
- `dataloader_persistent_workers`: False
- `skip_memory_metrics`: True
- `use_legacy_prediction_loop`: False
- `push_to_hub`: False
- `resume_from_checkpoint`: None
- `hub_model_id`: None
- `hub_strategy`: every_save
- `hub_private_repo`: False
- `hub_always_push`: False
- `gradient_checkpointing`: False
- `gradient_checkpointing_kwargs`: None
- `include_inputs_for_metrics`: False
- `eval_do_concat_batches`: True
- `fp16_backend`: auto
- `push_to_hub_model_id`: None
- `push_to_hub_organization`: None
- `mp_parameters`:
- `auto_find_batch_size`: False
- `full_determinism`: False
- `torchdynamo`: None
- `ray_scope`: last
- `ddp_timeout`: 1800
- `torch_compile`: False
- `torch_compile_backend`: None
- `torch_compile_mode`: None
- `dispatch_batches`: None
- `split_batches`: None
- `include_tokens_per_second`: False
- `include_num_input_tokens_seen`: False
- `neftune_noise_alpha`: None
- `optim_target_modules`: None
- `batch_eval_metrics`: False
- `batch_sampler`: no_duplicates
- `multi_dataset_batch_sampler`: proportional