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---
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: wav2vec2-large-mms-1b-turkish-colab
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: tr
split: test[:10]
args: tr
metrics:
- name: Wer
type: wer
value: 0.42857142857142855
---
<!-- 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-large-mms-1b-turkish-colab
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co./facebook/mms-1b-all) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4348
- Wer: 0.4286
## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.3297 | 0.12 | 100 | 0.5375 | 0.4571 |
| 0.2726 | 0.25 | 200 | 0.5256 | 0.4714 |
| 0.265 | 0.37 | 300 | 0.4696 | 0.4571 |
| 0.263 | 0.49 | 400 | 0.4405 | 0.4286 |
| 0.2574 | 0.61 | 500 | 0.4363 | 0.4143 |
| 0.2517 | 0.74 | 600 | 0.4592 | 0.4286 |
| 0.2454 | 0.86 | 700 | 0.4445 | 0.4143 |
| 0.2425 | 0.98 | 800 | 0.4348 | 0.4286 |
### Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
|