---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: Roberta-base-Rewritten-commit_messages_v2
  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_v2

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4196
- Accuracy: 0.7704
- F1: 0.7707
- Precision: 0.7811
- Recall: 0.7704

## 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: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.2288        | 0.09  | 100  | 0.7615          | 0.6716   | 0.6578 | 0.7461    | 0.6716 |
| 0.1103        | 0.17  | 200  | 0.6396          | 0.7453   | 0.7452 | 0.7609    | 0.7453 |
| 0.2204        | 0.26  | 300  | 1.3317          | 0.6596   | 0.6334 | 0.7863    | 0.6596 |
| 0.1872        | 0.34  | 400  | 0.8661          | 0.6333   | 0.5996 | 0.7712    | 0.6333 |
| 0.1261        | 0.43  | 500  | 1.9369          | 0.7130   | 0.7023 | 0.7906    | 0.7130 |
| 0.1902        | 0.52  | 600  | 2.2998          | 0.6823   | 0.6695 | 0.7573    | 0.6823 |
| 0.3639        | 0.6   | 700  | 4.0162          | 0.6915   | 0.6815 | 0.7562    | 0.6915 |
| 0.1655        | 0.69  | 800  | 2.2680          | 0.6859   | 0.6715 | 0.7705    | 0.6859 |
| 0.1534        | 0.77  | 900  | 2.7909          | 0.7951   | 0.7937 | 0.7959    | 0.7951 |
| 0.288         | 0.86  | 1000 | 2.9443          | 0.7752   | 0.7751 | 0.7920    | 0.7752 |
| 0.2261        | 0.95  | 1100 | 2.9976          | 0.7318   | 0.7267 | 0.7810    | 0.7318 |
| 0.162         | 1.03  | 1200 | 2.4699          | 0.8063   | 0.8067 | 0.8096    | 0.8063 |
| 0.0379        | 1.12  | 1300 | 2.6939          | 0.8051   | 0.8051 | 0.8051    | 0.8051 |
| 0.1852        | 1.2   | 1400 | 3.9005          | 0.7031   | 0.6940 | 0.7669    | 0.7031 |
| 0.1258        | 1.29  | 1500 | 2.6666          | 0.8023   | 0.8027 | 0.8042    | 0.8023 |
| 0.1707        | 1.38  | 1600 | 2.8308          | 0.7892   | 0.7892 | 0.7892    | 0.7892 |
| 0.0817        | 1.46  | 1700 | 3.6049          | 0.7573   | 0.7497 | 0.7700    | 0.7573 |
| 0.3516        | 1.55  | 1800 | 2.6816          | 0.7772   | 0.7777 | 0.7846    | 0.7772 |
| 0.5502        | 1.63  | 1900 | 2.2493          | 0.8131   | 0.8099 | 0.8203    | 0.8131 |
| 0.1531        | 1.72  | 2000 | 3.2802          | 0.7417   | 0.7407 | 0.7645    | 0.7417 |
| 0.1112        | 1.81  | 2100 | 1.9678          | 0.7748   | 0.7737 | 0.8010    | 0.7748 |
| 0.1617        | 1.89  | 2200 | 3.0694          | 0.7501   | 0.7490 | 0.7746    | 0.7501 |
| 0.1912        | 1.98  | 2300 | 3.2285          | 0.7529   | 0.7530 | 0.7659    | 0.7529 |
| 0.2725        | 2.06  | 2400 | 3.0008          | 0.7800   | 0.7805 | 0.7826    | 0.7800 |
| 0.1694        | 2.15  | 2500 | 3.5542          | 0.7290   | 0.7286 | 0.7459    | 0.7290 |
| 0.1283        | 2.24  | 2600 | 4.4577          | 0.7003   | 0.6944 | 0.7466    | 0.7003 |
| 0.1321        | 2.32  | 2700 | 3.1128          | 0.7350   | 0.7356 | 0.7411    | 0.7350 |
| 0.0           | 2.41  | 2800 | 4.2938          | 0.7222   | 0.7149 | 0.7828    | 0.7222 |
| 0.0871        | 2.49  | 2900 | 3.9750          | 0.7266   | 0.7237 | 0.7607    | 0.7266 |
| 0.0952        | 2.58  | 3000 | 3.7697          | 0.7437   | 0.7424 | 0.7690    | 0.7437 |
| 0.1034        | 2.67  | 3100 | 3.7283          | 0.7350   | 0.7312 | 0.7764    | 0.7350 |
| 0.2425        | 2.75  | 3200 | 3.4196          | 0.7704   | 0.7707 | 0.7811    | 0.7704 |


### Framework versions

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