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
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: 1.0029013539651837
wav2vec2-xls-r-300m-malayalam-colab-CV17.0
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: 1.6154
- Wer: 1.0029
- Cer: 0.4254
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: 3e-05
- 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 |
|---|---|---|---|---|---|
| 15.7515 | 3.1496 | 200 | 7.2856 | 1.0 | 1.0 |
| 5.2078 | 6.2992 | 400 | 3.9581 | 1.0 | 1.0 |
| 3.6268 | 9.4488 | 600 | 3.4876 | 1.0 | 0.9923 |
| 3.4082 | 12.5984 | 800 | 3.3891 | 1.0 | 0.9906 |
| 3.3259 | 15.7480 | 1000 | 3.3171 | 0.9984 | 0.9415 |
| 3.0224 | 18.8976 | 1200 | 2.6551 | 1.0 | 0.7845 |
| 2.1063 | 22.0472 | 1400 | 1.9206 | 0.9942 | 0.4722 |
| 1.564 | 25.1969 | 1600 | 1.6999 | 0.9916 | 0.4298 |
| 1.3323 | 28.3465 | 1800 | 1.6358 | 0.9990 | 0.4264 |
| 1.2413 | 31.4961 | 2000 | 1.6154 | 1.0029 | 0.4254 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1