File size: 1,708 Bytes
d6d9294 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 |
---
license: apache-2.0
base_model: mrm8488/bert-mini2bert-mini-finetuned-cnn_daily_mail-summarization
tags:
- generated_from_trainer
model-index:
- name: bert2bert
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert2bert
This model is a fine-tuned version of [mrm8488/bert-mini2bert-mini-finetuned-cnn_daily_mail-summarization](https://huggingface.co/mrm8488/bert-mini2bert-mini-finetuned-cnn_daily_mail-summarization) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1196
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.1386 | 1.0 | 3677 | 0.1256 |
| 0.1294 | 2.0 | 7355 | 0.1227 |
| 0.1233 | 3.0 | 11032 | 0.1210 |
| 0.1204 | 4.0 | 14710 | 0.1200 |
| 0.1191 | 5.0 | 18385 | 0.1196 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Tokenizers 0.15.2
|