metadata
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
datasets:
- ml-superb-subset
metrics:
- wer
model-index:
- name: w2v-bert-2.0-ml-superb-xty
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: ml-superb-subset
type: ml-superb-subset
config: xty
split: test
args: xty
metrics:
- name: Wer
type: wer
value: 1.3984915147705845
w2v-bert-2.0-ml-superb-xty
This model is a fine-tuned version of facebook/w2v-bert-2.0 on the ml-superb-subset dataset. It achieves the following results on the evaluation set:
- Loss: 2.3981
- Wer: 1.3985
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: 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: 30
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.5467 | 0.8219 | 30 | 2.8636 | 1.0 |
| 2.4639 | 1.6438 | 60 | 2.5298 | 1.0094 |
| 2.38 | 2.4658 | 90 | 2.4983 | 1.1263 |
| 2.2725 | 3.2877 | 120 | 2.4866 | 1.2319 |
| 2.2608 | 4.1096 | 150 | 2.5116 | 1.5405 |
| 2.2222 | 4.9315 | 180 | 2.4588 | 1.3300 |
| 2.2609 | 5.7534 | 210 | 2.4448 | 1.3451 |
| 2.1665 | 6.5753 | 240 | 2.4270 | 1.3199 |
| 2.1703 | 7.3973 | 270 | 2.4223 | 1.3576 |
| 2.1366 | 8.2192 | 300 | 2.4054 | 1.4085 |
| 2.123 | 9.0411 | 330 | 2.4006 | 1.4180 |
| 2.1331 | 9.8630 | 360 | 2.3981 | 1.3985 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1