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---
base_model: facebook/mms-1b-all
datasets:
- common_voice_17_0
library_name: transformers
license: cc-by-nc-4.0
metrics:
- wer
- bleu
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-mms-1b-CV17.0-training_set_variations
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: ta
split: validation[:5%]+validation[20%:25%]+validation[60%:65%]+validation[90%:]
args: ta
metrics:
- type: wer
value: 1.0594668189204621
name: Wer
- type: bleu
value: 0.0
name: Bleu
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-mms-1b-CV17.0-training_set_variations
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 8.6744
- Wer: 1.0595
- Cer: 0.7507
- Bleu: 0.0
## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.15
- training_steps: 2000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Bleu |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:----:|
| 8.9593 | 25.0 | 100 | 4.6860 | 1.0 | 0.9446 | 0.0 |
| 3.3283 | 50.0 | 200 | 5.0896 | 1.0199 | 0.8069 | 0.0 |
| 2.6345 | 75.0 | 300 | 6.0989 | 1.0176 | 0.7693 | 0.0 |
| 1.963 | 100.0 | 400 | 6.7363 | 1.0451 | 0.7518 | 0.0 |
| 1.3091 | 125.0 | 500 | 7.8085 | 1.0284 | 0.7587 | 0.0 |
| 0.912 | 150.0 | 600 | 8.6744 | 1.0595 | 0.7507 | 0.0 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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