---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: Roberta-base-Rewritten-commit_messages_v1
  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. -->

# Roberta-base-Rewritten-commit_messages_v1

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.0366
- Accuracy: 0.7334
- F1: 0.7333
- Precision: 0.7485
- Recall: 0.7334

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.211         | 0.09  | 100  | 0.5038          | 0.7716   | 0.7710 | 0.7712    | 0.7716 |
| 0.1021        | 0.17  | 200  | 1.4349          | 0.6967   | 0.6878 | 0.7575    | 0.6967 |
| 0.21          | 0.26  | 300  | 1.6924          | 0.6772   | 0.6621 | 0.7604    | 0.6772 |
| 0.3015        | 0.34  | 400  | 1.2524          | 0.7688   | 0.7689 | 0.7691    | 0.7688 |
| 0.0545        | 0.43  | 500  | 0.6203          | 0.7967   | 0.7944 | 0.7996    | 0.7967 |
| 0.2606        | 0.52  | 600  | 1.9708          | 0.7812   | 0.7816 | 0.7831    | 0.7812 |
| 0.2303        | 0.6   | 700  | 4.2551          | 0.7003   | 0.6877 | 0.7822    | 0.7003 |
| 0.3791        | 0.69  | 800  | 3.9563          | 0.6449   | 0.6287 | 0.7176    | 0.6449 |
| 0.1818        | 0.77  | 900  | 3.2710          | 0.7413   | 0.7382 | 0.7798    | 0.7413 |
| 0.2664        | 0.86  | 1000 | 3.1223          | 0.7541   | 0.7545 | 0.7637    | 0.7541 |
| 0.0975        | 0.95  | 1100 | 4.2953          | 0.6628   | 0.6504 | 0.7279    | 0.6628 |
| 0.0994        | 1.03  | 1200 | 3.0247          | 0.7577   | 0.7568 | 0.7808    | 0.7577 |
| 0.0           | 1.12  | 1300 | 4.3038          | 0.7094   | 0.7048 | 0.7515    | 0.7094 |
| 0.1308        | 1.2   | 1400 | 3.6026          | 0.7497   | 0.7502 | 0.7576    | 0.7497 |
| 0.0518        | 1.29  | 1500 | 3.1581          | 0.7629   | 0.7634 | 0.7669    | 0.7629 |
| 0.0444        | 1.38  | 1600 | 3.5891          | 0.7485   | 0.7481 | 0.7480    | 0.7485 |
| 0.0904        | 1.46  | 1700 | 3.5088          | 0.7206   | 0.7162 | 0.7224    | 0.7206 |
| 0.2481        | 1.55  | 1800 | 3.5703          | 0.7083   | 0.7077 | 0.7257    | 0.7083 |
| 0.2444        | 1.63  | 1900 | 2.8876          | 0.7740   | 0.7688 | 0.7829    | 0.7740 |
| 0.1379        | 1.72  | 2000 | 3.2268          | 0.7385   | 0.7336 | 0.7426    | 0.7385 |
| 0.1244        | 1.81  | 2100 | 3.4375          | 0.7413   | 0.7417 | 0.7519    | 0.7413 |
| 0.0826        | 1.89  | 2200 | 3.1960          | 0.7688   | 0.7689 | 0.7689    | 0.7688 |
| 0.1172        | 1.98  | 2300 | 3.0243          | 0.7784   | 0.7784 | 0.7784    | 0.7784 |
| 0.1066        | 2.06  | 2400 | 3.2134          | 0.7764   | 0.7769 | 0.7790    | 0.7764 |
| 0.0           | 2.15  | 2500 | 3.3545          | 0.7664   | 0.7670 | 0.7694    | 0.7664 |
| 0.1429        | 2.24  | 2600 | 3.7563          | 0.7393   | 0.7389 | 0.7574    | 0.7393 |
| 0.0451        | 2.32  | 2700 | 3.4993          | 0.7537   | 0.7540 | 0.7548    | 0.7537 |
| 0.0           | 2.41  | 2800 | 3.7249          | 0.7501   | 0.7504 | 0.7511    | 0.7501 |
| 0.0273        | 2.49  | 2900 | 4.2791          | 0.7190   | 0.7175 | 0.7434    | 0.7190 |
| 0.0789        | 2.58  | 3000 | 4.2166          | 0.7178   | 0.7161 | 0.7438    | 0.7178 |
| 0.0527        | 2.67  | 3100 | 4.0366          | 0.7334   | 0.7333 | 0.7485    | 0.7334 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1