---
license: mit
base_model: gpt2
tags:
- generated_from_trainer
model-index:
- name: MammoLLM_bz32_acc4_lr1e4_large_epoch20
  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. -->

# MammoLLM_bz32_acc4_lr1e4_large_epoch20

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0667

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 3.5007        | 0.48  | 500   | 2.1723          |
| 1.9621        | 0.96  | 1000  | 1.7328          |
| 1.6708        | 1.44  | 1500  | 1.5700          |
| 1.5458        | 1.92  | 2000  | 1.4780          |
| 1.453         | 2.4   | 2500  | 1.4207          |
| 1.4098        | 2.87  | 3000  | 1.3808          |
| 1.3492        | 3.35  | 3500  | 1.3499          |
| 1.3205        | 3.83  | 4000  | 1.3220          |
| 1.2694        | 4.31  | 4500  | 1.2945          |
| 1.2459        | 4.79  | 5000  | 1.2724          |
| 1.2006        | 5.27  | 5500  | 1.2482          |
| 1.1749        | 5.75  | 6000  | 1.2302          |
| 1.139         | 6.23  | 6500  | 1.2146          |
| 1.105         | 6.71  | 7000  | 1.1944          |
| 1.0754        | 7.19  | 7500  | 1.1791          |
| 1.0407        | 7.66  | 8000  | 1.1618          |
| 1.0188        | 8.14  | 8500  | 1.1497          |
| 0.9787        | 8.62  | 9000  | 1.1374          |
| 0.9652        | 9.1   | 9500  | 1.1300          |
| 0.9177        | 9.58  | 10000 | 1.1139          |
| 0.9165        | 10.06 | 10500 | 1.1088          |
| 0.8636        | 10.54 | 11000 | 1.0979          |
| 0.8693        | 11.02 | 11500 | 1.0909          |
| 0.812         | 11.5  | 12000 | 1.0895          |
| 0.8243        | 11.98 | 12500 | 1.0779          |
| 0.7734        | 12.46 | 13000 | 1.0796          |
| 0.7792        | 12.93 | 13500 | 1.0717          |
| 0.74          | 13.41 | 14000 | 1.0763          |
| 0.7403        | 13.89 | 14500 | 1.0681          |
| 0.7088        | 14.37 | 15000 | 1.0699          |
| 0.708         | 14.85 | 15500 | 1.0650          |
| 0.6846        | 15.33 | 16000 | 1.0684          |
| 0.6811        | 15.81 | 16500 | 1.0652          |
| 0.6644        | 16.29 | 17000 | 1.0688          |
| 0.6582        | 16.77 | 17500 | 1.0665          |
| 0.6512        | 17.25 | 18000 | 1.0669          |
| 0.6433        | 17.72 | 18500 | 1.0663          |
| 0.6403        | 18.2  | 19000 | 1.0668          |
| 0.6347        | 18.68 | 19500 | 1.0666          |
| 0.6318        | 19.16 | 20000 | 1.0668          |
| 0.6304        | 19.64 | 20500 | 1.0667          |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.3
- Tokenizers 0.13.3