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---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
- bleu
model-index:
- name: wav2vec2-mms-1b-CV17.0-training_set_variations
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: ta
split: validation
args: ta
metrics:
- name: Wer
type: wer
value: 0.38488334784800843
- name: Bleu
type: bleu
value: 0.3848277074951031
---
<!-- 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: 0.2335
- Wer: 0.3849
- Cer: 0.0627
- Bleu: 0.3848
## 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 |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|:------:|
| 12.5537 | 1.5625 | 50 | 3.9513 | 1.0006 | 0.9854 | 0.0 |
| 2.2034 | 3.125 | 100 | 0.3019 | 0.4137 | 0.0683 | 0.3510 |
| 0.226 | 4.6875 | 150 | 0.2305 | 0.3794 | 0.0623 | 0.3981 |
| 0.1904 | 6.25 | 200 | 0.2262 | 0.3776 | 0.0618 | 0.3988 |
| 0.1798 | 7.8125 | 250 | 0.2275 | 0.3760 | 0.0621 | 0.4040 |
| 0.1724 | 9.375 | 300 | 0.2399 | 0.4021 | 0.0659 | 0.3610 |
| 0.1791 | 10.9375 | 350 | 0.2310 | 0.3883 | 0.0635 | 0.3797 |
| 0.1678 | 12.5 | 400 | 0.2405 | 0.3961 | 0.0666 | 0.3722 |
| 0.1527 | 14.0625 | 450 | 0.2335 | 0.3849 | 0.0627 | 0.3848 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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