metadata
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: wav2vec2-xls-r-300m-malayalam-colab-CV17.0-v2
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: ml
split: test
args: ml
metrics:
- name: Wer
type: wer
value: 0.7946486137975499
wav2vec2-xls-r-300m-malayalam-colab-CV17.0-v2
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.9415
- Wer: 0.7946
- Cer: 0.1990
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_ratio: 0.15
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 8.3824 | 3.1496 | 200 | 3.5244 | 1.0 | 1.0 |
| 2.8615 | 6.2992 | 400 | 1.4480 | 0.9716 | 0.3680 |
| 0.8112 | 9.4488 | 600 | 0.9231 | 0.9188 | 0.2573 |
| 0.4211 | 12.5984 | 800 | 0.9136 | 0.8843 | 0.2477 |
| 0.2862 | 15.7480 | 1000 | 0.9257 | 0.8533 | 0.2370 |
| 0.21 | 18.8976 | 1200 | 0.9450 | 0.8185 | 0.2188 |
| 0.1772 | 22.0472 | 1400 | 0.9285 | 0.8343 | 0.2151 |
| 0.1432 | 25.1969 | 1600 | 0.9596 | 0.8262 | 0.2110 |
| 0.117 | 28.3465 | 1800 | 0.9419 | 0.7985 | 0.2026 |
| 0.1047 | 31.4961 | 2000 | 0.9415 | 0.7946 | 0.1990 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1