metadata
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: model_mms
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: tr
split: test[:100]
args: tr
metrics:
- name: Wer
type: wer
value: 0.3283018867924528
model_mms
This model is a fine-tuned version of facebook/mms-1b-all on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2666
- Wer: 0.3283
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: 0.001
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.0741 | 0.12 | 100 | 0.3252 | 0.3698 |
| 0.2837 | 0.24 | 200 | 0.2980 | 0.3509 |
| 0.2725 | 0.36 | 300 | 0.2808 | 0.3566 |
| 0.2727 | 0.47 | 400 | 0.2893 | 0.3509 |
| 0.2721 | 0.59 | 500 | 0.2806 | 0.3377 |
| 0.2602 | 0.71 | 600 | 0.2832 | 0.3377 |
| 0.2631 | 0.83 | 700 | 0.2740 | 0.3396 |
| 0.2528 | 0.95 | 800 | 0.2666 | 0.3283 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0