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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
args: ta
metrics:
- type: wer
value: 0.45588302699729566
name: Wer
- type: bleu
value: 0.30120570288375
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: 0.4242
- Wer: 0.4559
- Cer: 0.0764
- Bleu: 0.3012
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 13.1596 | 12.5 | 50 | 6.8694 | 1.0 | 0.9625 | 0.0 |
| 3.2131 | 25.0 | 100 | 0.4085 | 0.4707 | 0.0784 | 0.2830 |
| 0.1719 | 37.5 | 150 | 0.2583 | 0.3920 | 0.0650 | 0.3818 |
| 0.0962 | 50.0 | 200 | 0.2869 | 0.4118 | 0.0682 | 0.3547 |
| 0.0648 | 62.5 | 250 | 0.3209 | 0.4213 | 0.0696 | 0.3435 |
| 0.0613 | 75.0 | 300 | 0.3404 | 0.4454 | 0.0742 | 0.3200 |
| 0.0515 | 87.5 | 350 | 0.3744 | 0.4385 | 0.0734 | 0.3289 |
| 0.0426 | 100.0 | 400 | 0.3835 | 0.4479 | 0.0748 | 0.3078 |
| 0.0384 | 112.5 | 450 | 0.3776 | 0.4432 | 0.0746 | 0.3243 |
| 0.0363 | 125.0 | 500 | 0.4053 | 0.4371 | 0.0732 | 0.3251 |
| 0.0385 | 137.5 | 550 | 0.4225 | 0.4520 | 0.0772 | 0.3115 |
| 0.0343 | 150.0 | 600 | 0.4295 | 0.4463 | 0.0758 | 0.3167 |
| 0.0371 | 162.5 | 650 | 0.4242 | 0.4559 | 0.0764 | 0.3012 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
|