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---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
datasets:
- common_voice_6_1
metrics:
- wer
base_model: facebook/mms-1b-all
model-index:
- name: wav2vec2-large-mms-1b-turkish-colab-test
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: common_voice_6_1
type: common_voice_6_1
config: tr
split: test
args: tr
metrics:
- type: wer
value: 0.22040649576141355
name: Wer
---
<!-- 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-test
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the common_voice_6_1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1534
- Wer: 0.2204
## 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: 100
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.5985 | 0.92 | 100 | 0.1805 | 0.2490 |
| 0.2839 | 1.83 | 200 | 0.1657 | 0.2350 |
| 0.2662 | 2.75 | 300 | 0.1579 | 0.2274 |
| 0.2413 | 3.67 | 400 | 0.1534 | 0.2204 |
### Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3
|