metadata
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- automatic-speech-recognition
- natbed
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v-bert-bem-natbed-combined-model
results: []
w2v-bert-bem-natbed-combined-model
This model is a fine-tuned version of facebook/w2v-bert-2.0 on the NATBED - BEM dataset. It achieves the following results on the evaluation set:
- Loss: 0.6289
- Wer: 0.6078
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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 30.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.0078 | 0.5006 | 200 | 0.9815 | 0.8201 |
| 0.8769 | 1.0013 | 400 | 0.9823 | 1.0433 |
| 0.805 | 1.5019 | 600 | 0.8306 | 0.8606 |
| 0.8141 | 2.0025 | 800 | 0.7548 | 0.7196 |
| 0.7132 | 2.5031 | 1000 | 0.7485 | 0.6932 |
| 0.7058 | 3.0038 | 1200 | 0.7280 | 0.6917 |
| 0.6563 | 3.5044 | 1400 | 0.7046 | 0.7045 |
| 0.6232 | 4.0050 | 1600 | 0.7186 | 0.7409 |
| 0.6093 | 4.5056 | 1800 | 0.7048 | 0.6434 |
| 0.5767 | 5.0063 | 2000 | 0.6521 | 0.6474 |
| 0.5628 | 5.5069 | 2200 | 0.6322 | 0.6018 |
| 0.5569 | 6.0075 | 2400 | 0.6289 | 0.6078 |
| 0.5156 | 6.5081 | 2600 | 0.6504 | 0.6374 |
| 0.5074 | 7.0088 | 2800 | 0.6638 | 0.6222 |
| 0.4906 | 7.5094 | 3000 | 0.6744 | 0.5884 |
Framework versions
- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0