metadata
library_name: peft
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
datasets:
- biobert_json
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: finetuned_model
results: []
finetuned_model
This model is a fine-tuned version of FacebookAI/xlm-roberta-large on the biobert_json dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Precision: 0.0025
- Recall: 0.0130
- F1: 0.0042
- Accuracy: 0.0207
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0 | 1.0 | 306 | nan | 0.0025 | 0.0130 | 0.0042 | 0.0207 |
| 0.0 | 2.0 | 612 | nan | 0.0025 | 0.0130 | 0.0042 | 0.0207 |
| 0.0 | 3.0 | 918 | nan | 0.0025 | 0.0130 | 0.0042 | 0.0207 |
| 0.0 | 4.0 | 1224 | nan | 0.0025 | 0.0130 | 0.0042 | 0.0207 |
| 0.0 | 5.0 | 1530 | nan | 0.0025 | 0.0130 | 0.0042 | 0.0207 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3