---
license: mit
base_model: gpt2
tags:
- generated_from_trainer
model-index:
- name: MammoLLM2
  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. -->

# MammoLLM2

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: 1.6666

## 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: 0.0005
- 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: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.7888        | 1.24  | 500   | 1.0984          |
| 1.1179        | 2.49  | 1000  | 1.0209          |
| 1.0556        | 3.73  | 1500  | 0.9913          |
| 1.01          | 4.98  | 2000  | 0.9653          |
| 0.9723        | 6.22  | 2500  | 0.9608          |
| 0.9425        | 7.47  | 3000  | 0.9455          |
| 0.9149        | 8.71  | 3500  | 0.9391          |
| 0.8877        | 9.96  | 4000  | 0.9253          |
| 0.8478        | 11.2  | 4500  | 0.9317          |
| 0.8142        | 12.45 | 5000  | 0.9313          |
| 0.7814        | 13.69 | 5500  | 0.9299          |
| 0.7494        | 14.93 | 6000  | 0.9330          |
| 0.7071        | 16.18 | 6500  | 0.9588          |
| 0.6774        | 17.42 | 7000  | 0.9704          |
| 0.6511        | 18.67 | 7500  | 0.9828          |
| 0.6275        | 19.91 | 8000  | 1.0007          |
| 0.595         | 21.16 | 8500  | 1.0432          |
| 0.5698        | 22.4  | 9000  | 1.0641          |
| 0.546         | 23.65 | 9500  | 1.0879          |
| 0.523         | 24.89 | 10000 | 1.0982          |
| 0.4913        | 26.14 | 10500 | 1.1579          |
| 0.4622        | 27.38 | 11000 | 1.1923          |
| 0.4378        | 28.62 | 11500 | 1.2152          |
| 0.4131        | 29.87 | 12000 | 1.2440          |
| 0.3846        | 31.11 | 12500 | 1.3181          |
| 0.3592        | 32.36 | 13000 | 1.3497          |
| 0.3411        | 33.6  | 13500 | 1.3847          |
| 0.324         | 34.85 | 14000 | 1.4070          |
| 0.3061        | 36.09 | 14500 | 1.4755          |
| 0.2903        | 37.34 | 15000 | 1.5078          |
| 0.2795        | 38.58 | 15500 | 1.5351          |
| 0.2701        | 39.83 | 16000 | 1.5639          |
| 0.2605        | 41.07 | 16500 | 1.5972          |
| 0.2521        | 42.31 | 17000 | 1.6191          |
| 0.2467        | 43.56 | 17500 | 1.6300          |
| 0.2425        | 44.8  | 18000 | 1.6453          |
| 0.2386        | 46.05 | 18500 | 1.6554          |
| 0.2356        | 47.29 | 19000 | 1.6628          |
| 0.2344        | 48.54 | 19500 | 1.6663          |
| 0.2333        | 49.78 | 20000 | 1.6666          |


### Framework versions

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