metadata
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- automatic-speech-recognition
- CLEAR-Global/luo_19h
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v-bert-2.0-luo_cv_fleurs_19h-v3
results: []
w2v-bert-2.0-luo_cv_fleurs_19h-v3
This model is a fine-tuned version of facebook/w2v-bert-2.0 on the CLEAR-GLOBAL/LUO_19H - NA dataset. It achieves the following results on the evaluation set:
- Loss: 0.2850
- Wer: 0.3100
- Cer: 0.0950
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 100000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.9185 | 6.4935 | 1000 | 0.8056 | 0.6817 | 0.2146 |
| 0.3338 | 12.9870 | 2000 | 0.4123 | 0.4070 | 0.1262 |
| 0.1888 | 19.4805 | 3000 | 0.3017 | 0.3492 | 0.1042 |
| 0.1032 | 25.9740 | 4000 | 0.2851 | 0.3100 | 0.0946 |
| 0.0541 | 32.4675 | 5000 | 0.3172 | 0.3060 | 0.0946 |
| 0.0284 | 38.9610 | 6000 | 0.3164 | 0.2897 | 0.0912 |
| 0.0145 | 45.4545 | 7000 | 0.3478 | 0.2879 | 0.0904 |
| 0.0176 | 51.9481 | 8000 | 0.3971 | 0.3113 | 0.0933 |
| 0.0051 | 58.4416 | 9000 | 0.4149 | 0.3051 | 0.0905 |
Framework versions
- Transformers 4.48.1
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1