metadata
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: []
modelofine2
This model is a fine-tuned version of 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