---
license: apache-2.0
base_model: projecte-aina/roberta-base-ca-v2-cased-te
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: modelofine2
  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. -->

# modelofine2

This model is a fine-tuned version of [projecte-aina/roberta-base-ca-v2-cased-te](https://huggingface.co/projecte-aina/roberta-base-ca-v2-cased-te) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6811
- Accuracy: 0.6471

## 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: 7e-05
- train_batch_size: 20
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 60
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 3.2258  | 100  | 2.7256          | 0.5546   |
| No log        | 6.4516  | 200  | 2.7585          | 0.5714   |
| No log        | 9.6774  | 300  | 2.9830          | 0.5378   |
| No log        | 12.9032 | 400  | 3.8506          | 0.5042   |
| 0.0468        | 16.1290 | 500  | 3.4211          | 0.5294   |
| 0.0468        | 19.3548 | 600  | 2.7938          | 0.5882   |
| 0.0468        | 22.5806 | 700  | 2.9805          | 0.6050   |
| 0.0468        | 25.8065 | 800  | 2.9111          | 0.5882   |
| 0.0468        | 29.0323 | 900  | 2.7054          | 0.6134   |
| 0.0358        | 32.2581 | 1000 | 2.6811          | 0.6471   |
| 0.0358        | 35.4839 | 1100 | 2.8372          | 0.6134   |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.1.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1