metadata
library_name: transformers
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: mt5_lr3e-05_bs4_ep3
results: []
mt5_lr3e-05_bs4_ep3
This model is a fine-tuned version of google/mt5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5076
- Precision: 0.5353
- Recall: 0.4164
- F1: 0.4684
- Accuracy: 0.7817
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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 2.2373 | 1.0 | 860 | 0.5532 | 0.5208 | 0.2941 | 0.3759 | 0.7744 |
| 0.8792 | 2.0 | 1720 | 0.5793 | 0.4464 | 0.6333 | 0.5237 | 0.7339 |
| 0.7574 | 3.0 | 2580 | 0.5076 | 0.5353 | 0.4164 | 0.4684 | 0.7817 |
Framework versions
- Transformers 4.47.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1