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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: 0.4958060228262364
name: Wer
- type: bleu
value: 0.2629057639184852
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: 0.5099
- Wer: 0.4958
- Cer: 0.0885
- Bleu: 0.2629
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 11.4061 | 50.0 | 50 | 4.6415 | 1.0007 | 0.9640 | 0.0 |
| 1.789 | 100.0 | 100 | 0.3026 | 0.4457 | 0.0734 | 0.3064 |
| 0.08 | 150.0 | 150 | 0.3223 | 0.4304 | 0.0711 | 0.3275 |
| 0.0473 | 200.0 | 200 | 0.3547 | 0.4426 | 0.0742 | 0.3156 |
| 0.0364 | 250.0 | 250 | 0.3786 | 0.4556 | 0.0761 | 0.2972 |
| 0.0298 | 300.0 | 300 | 0.4070 | 0.4629 | 0.0800 | 0.2875 |
| 0.0279 | 350.0 | 350 | 0.4190 | 0.4688 | 0.0799 | 0.2864 |
| 0.0253 | 400.0 | 400 | 0.4353 | 0.4755 | 0.0818 | 0.2757 |
| 0.0198 | 450.0 | 450 | 0.4808 | 0.5066 | 0.0887 | 0.2432 |
| 0.0216 | 500.0 | 500 | 0.4699 | 0.4780 | 0.0815 | 0.2777 |
| 0.0194 | 550.0 | 550 | 0.4745 | 0.4895 | 0.0877 | 0.2643 |
| 0.0201 | 600.0 | 600 | 0.5035 | 0.4971 | 0.0881 | 0.2647 |
| 0.0153 | 650.0 | 650 | 0.5099 | 0.4958 | 0.0885 | 0.2629 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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