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---
language:
- ta
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_6_1
- generated_from_trainer
datasets:
- common_voice_6_1
metrics:
- wer
model-index:
- name: wav2vec2-common_voice-ta
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: MOZILLA-FOUNDATION/COMMON_VOICE_6_1 - TA
type: common_voice_6_1
config: ta
split: test
args: 'Config: ta, Training split: train+validation, Eval split: test'
metrics:
- name: Wer
type: wer
value: 0.7095686384712659
---
<!-- 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-common_voice-ta
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the MOZILLA-FOUNDATION/COMMON_VOICE_6_1 - TA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6563
- Wer: 0.7096
## 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: 0.0003
- 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_steps: 500
- num_epochs: 15.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log | 0.84 | 100 | 4.3941 | 1.0 |
| No log | 1.69 | 200 | 3.2005 | 1.0 |
| No log | 2.53 | 300 | 2.7844 | 1.0145 |
| No log | 3.38 | 400 | 0.8691 | 1.0003 |
| 4.317 | 4.22 | 500 | 0.6846 | 0.8394 |
| 4.317 | 5.06 | 600 | 0.6270 | 0.7790 |
| 4.317 | 5.91 | 700 | 0.5935 | 0.7802 |
| 4.317 | 6.75 | 800 | 0.5701 | 0.7812 |
| 4.317 | 7.59 | 900 | 0.5649 | 0.7891 |
| 0.3656 | 8.44 | 1000 | 0.6092 | 0.8178 |
| 0.3656 | 9.28 | 1100 | 0.6093 | 0.7721 |
| 0.3656 | 10.13 | 1200 | 0.6154 | 0.7287 |
| 0.3656 | 10.97 | 1300 | 0.6284 | 0.7408 |
| 0.3656 | 11.81 | 1400 | 0.6343 | 0.7143 |
| 0.1681 | 12.66 | 1500 | 0.6523 | 0.7363 |
| 0.1681 | 13.5 | 1600 | 0.6543 | 0.7139 |
| 0.1681 | 14.35 | 1700 | 0.6599 | 0.7094 |
### Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
|