---
base_model: agusbrusco/bert_adaptation_martin_fierro
tags:
- generated_from_trainer
model-index:
- name: bert_adaptation_peppa_pig
  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. -->

# bert_adaptation_peppa_pig

This model is a fine-tuned version of [agusbrusco/bert_adaptation_martin_fierro](https://huggingface.co/agusbrusco/bert_adaptation_martin_fierro) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7256

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.1797        | 1.0   | 70   | 2.5543          |
| 2.3384        | 2.0   | 140  | 2.5390          |
| 2.2091        | 3.0   | 210  | 2.3234          |
| 1.9889        | 4.0   | 280  | 2.0118          |
| 1.9684        | 5.0   | 350  | 2.0932          |
| 1.8202        | 6.0   | 420  | 1.8260          |
| 1.6815        | 7.0   | 490  | 1.8649          |
| 1.6206        | 8.0   | 560  | 2.0040          |
| 1.5818        | 9.0   | 630  | 1.8634          |
| 1.529         | 10.0  | 700  | 1.9388          |
| 1.5113        | 11.0  | 770  | 1.7657          |
| 1.3993        | 12.0  | 840  | 1.7469          |
| 1.4784        | 13.0  | 910  | 1.7877          |
| 1.434         | 14.0  | 980  | 1.8657          |
| 1.3549        | 15.0  | 1050 | 1.8388          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0