metadata
license: cc-by-nc-4.0
base_model: facebook/mms-1b
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: results
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: audiofolder
type: audiofolder
config: default
split: test
args: default
metrics:
- name: Wer
type: wer
value: 0.5377405032067094
results
This model is a fine-tuned version of facebook/mms-1b on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.3647
- Wer: 0.5377
- Cer: 0.2651
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 500
- num_epochs: 13
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 3.4128 | 1.6495 | 40 | 3.2154 | 1.0 | 1.0 |
| 2.8944 | 3.2990 | 80 | 2.7463 | 0.9896 | 0.9891 |
| 1.5023 | 4.9485 | 120 | 1.4803 | 0.6971 | 0.3166 |
| 1.1458 | 6.5979 | 160 | 1.2789 | 0.5580 | 0.2638 |
| 0.9619 | 8.2474 | 200 | 1.2553 | 0.5639 | 0.2702 |
| 0.8777 | 9.8969 | 240 | 1.2722 | 0.5215 | 0.2633 |
| 0.7732 | 11.5464 | 280 | 1.3647 | 0.5377 | 0.2651 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1