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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: 0.4582664894348444
name: Wer
- type: bleu
value: 0.3001349308741465
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: 0.4355
- Wer: 0.4583
- Cer: 0.0787
- Bleu: 0.3001
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 12.8763 | 25.0 | 50 | 4.9690 | 1.0000 | 0.9319 | 0.0 |
| 2.2038 | 50.0 | 100 | 0.3040 | 0.4239 | 0.0696 | 0.3337 |
| 0.1153 | 75.0 | 150 | 0.2911 | 0.4134 | 0.0685 | 0.3474 |
| 0.0557 | 100.0 | 200 | 0.3344 | 0.4333 | 0.0718 | 0.3271 |
| 0.0448 | 125.0 | 250 | 0.3486 | 0.4403 | 0.0743 | 0.3213 |
| 0.0382 | 150.0 | 300 | 0.3938 | 0.4499 | 0.0762 | 0.3102 |
| 0.0364 | 175.0 | 350 | 0.3927 | 0.4525 | 0.0778 | 0.3045 |
| 0.0286 | 200.0 | 400 | 0.3883 | 0.4417 | 0.0744 | 0.3173 |
| 0.0293 | 225.0 | 450 | 0.4235 | 0.4656 | 0.0794 | 0.2913 |
| 0.0296 | 250.0 | 500 | 0.4432 | 0.4710 | 0.0817 | 0.2771 |
| 0.0302 | 275.0 | 550 | 0.4266 | 0.4524 | 0.0765 | 0.3016 |
| 0.0252 | 300.0 | 600 | 0.4376 | 0.4717 | 0.0815 | 0.2793 |
| 0.0216 | 325.0 | 650 | 0.4355 | 0.4583 | 0.0787 | 0.3001 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
|