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---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: wav2vec2-Malayalam
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: ml
split: None
args: ml
metrics:
- name: Wer
type: wer
value: 0.908768536428111
---
<!-- 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-Malayalam
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7479
- Wer: 0.9088
## 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: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 8.6036 | 1.5748 | 100 | 6.5081 | 1.0 |
| 3.5056 | 3.1496 | 200 | 3.5634 | 1.0 |
| 3.4952 | 4.7244 | 300 | 3.4927 | 1.0 |
| 3.3772 | 6.2992 | 400 | 3.3696 | 1.0 |
| 3.1849 | 7.8740 | 500 | 3.1735 | 1.0 |
| 1.3056 | 9.4488 | 600 | 1.2938 | 1.1167 |
| 0.8162 | 11.0236 | 700 | 0.8301 | 1.0190 |
| 0.6022 | 12.5984 | 800 | 0.7678 | 0.9929 |
| 0.454 | 14.1732 | 900 | 0.7514 | 0.9832 |
| 0.4104 | 15.7480 | 1000 | 0.7168 | 0.9452 |
| 0.3616 | 17.3228 | 1100 | 0.7297 | 0.9571 |
| 0.2951 | 18.8976 | 1200 | 0.6925 | 0.9555 |
| 0.2667 | 20.4724 | 1300 | 0.7254 | 0.9400 |
| 0.2707 | 22.0472 | 1400 | 0.7498 | 0.9101 |
| 0.2263 | 23.6220 | 1500 | 0.7093 | 0.9120 |
| 0.1933 | 25.1969 | 1600 | 0.7396 | 0.9091 |
| 0.2168 | 26.7717 | 1700 | 0.7417 | 0.9046 |
| 0.2112 | 28.3465 | 1800 | 0.7479 | 0.9088 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1.dev0
- Tokenizers 0.19.1
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