2504separado4
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: 0.7346
- Accuracy: 0.8403
- Precision: 0.8451
- Recall: 0.8403
- F1: 0.8398
- Ratio: 0.5588
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: 16
- eval_batch_size: 8
- 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_ratio: 0.06
- num_epochs: 4
- label_smoothing_factor: 0.1
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Ratio |
---|---|---|---|---|---|---|---|---|
0.3339 | 0.9870 | 38 | 0.8160 | 0.8151 | 0.8243 | 0.8151 | 0.8138 | 0.5840 |
0.324 | 2.0 | 77 | 0.7346 | 0.8403 | 0.8451 | 0.8403 | 0.8398 | 0.5588 |
0.3548 | 2.9870 | 115 | 0.7188 | 0.8319 | 0.8343 | 0.8319 | 0.8316 | 0.5420 |
0.3957 | 3.9481 | 152 | 0.6996 | 0.8361 | 0.8367 | 0.8361 | 0.8361 | 0.5210 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for adriansanz/2504separado4
Base model
projecte-aina/roberta-base-ca-v2-cased-te