metadata

base_model: EleutherAI/pythia-31m
tags:
  - generated_from_trainer
metrics:
  - accuracy
inference:
  parameters:
    max_new_tokens: 64
    do_sample: true
    repetition_penalty: 1.1
    no_repeat_ngram_size: 5
    eta_cutoff: 0.001
widget:
  - text: My name is El Microondas the Wise and
    example_title: El Microondas
  - text: Kennesaw State University is a public
    example_title: Kennesaw State University
  - text: >-
      Bungie Studios is an American video game developer. They are most famous
      for developing the award winning Halo series of video games. They also
      made Destiny. The studio was founded
    example_title: Bungie
  - text: The Mona Lisa is a world-renowned painting created by
    example_title: Mona Lisa
  - text: >-
      The Harry Potter series, written by J.K. Rowling, begins with the book
      titled
    example_title: Harry Potter Series
  - text: >-
      Question: I have cities, but no houses. I have mountains, but no trees. I
      have water, but no fish. What am I?

      Answer:
    example_title: Riddle
  - text: The process of photosynthesis involves the conversion of
    example_title: Photosynthesis
  - text: >-
      Jane went to the store to buy some groceries. She picked up apples,
      oranges, and a loaf of bread. When she got home, she realized she forgot
    example_title: Story Continuation
  - text: >-
      Problem 2: If a train leaves Station A at 9:00 AM and travels at 60 mph,
      and another train leaves Station B at 10:00 AM and travels at 80 mph, when
      will they meet if the distance between the stations is 300 miles?

      To determine
    example_title: Math Problem
  - text: In the context of computer programming, an algorithm is
    example_title: Algorithm Definition
pipeline_tag: text-generation
license: apache-2.0
language:
  - en
datasets:
  - pszemraj/simpleRW-lite

BL-pythia-31m-simpleRW-lite-2048-scratch

This model is a fine-tuned version of EleutherAI/pythia-31m on the None dataset. It achieves the following results on the evaluation set:

Loss: 4.7136
Accuracy: 0.2662

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

2040 ***** eval metrics *****
2041   epoch                   =        3.0
2042   eval_accuracy           =     0.2668
2043   eval_loss               =     4.7076
2044   eval_runtime            = 0:00:21.04
2045   eval_samples            =        500
2046   eval_samples_per_second =     23.759
2047   eval_steps_per_second   =      11.88
2048   perplexity              =   110.7897

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.0005
train_batch_size: 2
eval_batch_size: 2
seed: 80085
gradient_accumulation_steps: 64
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-07
lr_scheduler_type: inverse_sqrt
lr_scheduler_warmup_ratio: 0.05
num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
7.0159	0.13	100	7.1022	0.1180
6.2257	0.27	200	6.3526	0.1508
5.8611	0.4	300	5.9888	0.1735
5.5514	0.54	400	5.7552	0.1855
5.3824	0.67	500	5.5883	0.1948
5.344	0.81	600	5.4697	0.2017
5.1925	0.94	700	5.3717	0.2073
5.0814	1.08	800	5.2932	0.2121
5.0865	1.21	900	5.2280	0.2162
4.9602	1.35	1000	5.1672	0.2207
4.957	1.48	1100	5.1144	0.2247
4.8489	1.62	1200	5.0617	0.2299
4.79	1.75	1300	5.0122	0.2349
4.8005	1.89	1400	4.9637	0.2400
4.7409	2.02	1500	4.9216	0.2448
4.6674	2.16	1600	4.8815	0.2488
4.6729	2.29	1700	4.8475	0.2526
4.7071	2.43	1800	4.8156	0.2555
4.4937	2.56	1900	4.7841	0.2588
4.5153	2.7	2000	4.7573	0.2615
4.5512	2.83	2100	4.7345	0.2637
4.5153	2.96	2200	4.7136	0.2662

Framework versions

Transformers 4.34.0.dev0
Pytorch 2.2.0.dev20230915+cu118
Datasets 2.14.5
Tokenizers 0.13.3