metadata
library_name: peft
base_model: castorini/afriteva_small
tags:
- generated_from_trainer
metrics:
- bleu
- f1
- wer
model-index:
- name: afriteva_small_trial2
results: []
afriteva_small_trial2
This model is a fine-tuned version of castorini/afriteva_small on the None dataset. It achieves the following results on the evaluation set:
- Bleu: 0.6835
- F1: 0.8468
- Wer: 0.1892
- Cer: 0.0704
- Meteor: 0.8278
- Loss: 0.1053
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: 0.0005
- 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: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Bleu | F1 | Wer | Cer | Meteor | Validation Loss |
|---|---|---|---|---|---|---|---|---|
| 0.1696 | 1.0 | 12500 | 0.6487 | 0.8307 | 0.2306 | 0.0982 | 0.8035 | 0.1195 |
| 0.1549 | 2.0 | 25000 | 0.6716 | 0.8410 | 0.2024 | 0.0792 | 0.8202 | 0.1104 |
| 0.1436 | 3.0 | 37500 | 0.6835 | 0.8468 | 0.1892 | 0.0704 | 0.8278 | 0.1053 |
Framework versions
- PEFT 0.15.2
- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1