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-large-xls-r-300m-test1yakutsi-colab
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: sah
split: test
args: sah
metrics:
- name: Wer
type: wer
value: 0.4245327102803738
pipeline_tag: automatic-speech-recognition
wav2vec2-large-xls-r-300m-test1yakutsi-colab
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: 0.4509
- Wer: 0.4245
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: 0.0002
- 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: 250
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.1089 | 1.1707 | 120 | 2.9271 | 1.0 |
| 2.1217 | 2.3415 | 240 | 0.8076 | 0.7261 |
| 0.5442 | 3.5122 | 360 | 0.4935 | 0.5490 |
| 0.3041 | 4.6829 | 480 | 0.4464 | 0.4832 |
| 0.2184 | 5.8537 | 600 | 0.4263 | 0.4554 |
| 0.1675 | 7.0244 | 720 | 0.4416 | 0.4488 |
| 0.138 | 8.1951 | 840 | 0.4512 | 0.4380 |
| 0.1167 | 9.3659 | 960 | 0.4509 | 0.4245 |
Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1