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---
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
datasets:
- common_voice_6_1
metrics:
- wer
model-index:
- name: wav2vec2-large-mms-1b-thai-colab
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_6_1
type: common_voice_6_1
config: th
split: test
args: th
metrics:
- name: Wer
type: wer
value: 0.7234125438254773
---
<!-- 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-thai-colab
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: 0.2452
- Wer: 0.7234
## 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: 8
- 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
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 8.0794 | 0.17 | 100 | 0.3832 | 0.8329 |
| 0.561 | 0.33 | 200 | 0.3162 | 0.8099 |
| 0.5132 | 0.5 | 300 | 0.2907 | 0.7842 |
| 0.5015 | 0.66 | 400 | 0.2954 | 0.7998 |
| 0.5126 | 0.83 | 500 | 0.2812 | 0.7924 |
| 0.5182 | 0.99 | 600 | 0.2782 | 0.7631 |
| 0.4459 | 1.16 | 700 | 0.2735 | 0.7526 |
| 0.4694 | 1.32 | 800 | 0.2716 | 0.7628 |
| 0.4576 | 1.49 | 900 | 0.2649 | 0.7538 |
| 0.4749 | 1.65 | 1000 | 0.2614 | 0.7503 |
| 0.4282 | 1.82 | 1100 | 0.2687 | 0.7464 |
| 0.4009 | 1.98 | 1200 | 0.2622 | 0.7480 |
| 0.3976 | 2.15 | 1300 | 0.2619 | 0.7421 |
| 0.4306 | 2.31 | 1400 | 0.2620 | 0.7538 |
| 0.4413 | 2.48 | 1500 | 0.2551 | 0.7515 |
| 0.3888 | 2.64 | 1600 | 0.2545 | 0.7339 |
| 0.4213 | 2.81 | 1700 | 0.2541 | 0.7316 |
| 0.3945 | 2.98 | 1800 | 0.2507 | 0.7246 |
| 0.3765 | 3.14 | 1900 | 0.2495 | 0.7234 |
| 0.3859 | 3.31 | 2000 | 0.2498 | 0.7269 |
| 0.3931 | 3.47 | 2100 | 0.2469 | 0.7250 |
| 0.3737 | 3.64 | 2200 | 0.2470 | 0.7242 |
| 0.3716 | 3.8 | 2300 | 0.2454 | 0.7219 |
| 0.3582 | 3.97 | 2400 | 0.2452 | 0.7234 |
### Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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