|
--- |
|
language: |
|
- ia |
|
license: apache-2.0 |
|
tags: |
|
- automatic-speech-recognition |
|
- generated_from_trainer |
|
- hf-asr-leaderboard |
|
- robust-speech-event |
|
- mozilla-foundation/common_voice_8_0 |
|
- robust-speech-event |
|
datasets: |
|
- mozilla-foundation/common_voice_8_0 |
|
model-index: |
|
- name: wav2vec2-large-xls-r-300m-ia |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: Common Voice 8 |
|
type: mozilla-foundation/common_voice_8_0 |
|
args: ia |
|
metrics: |
|
- name: Test WER using LM |
|
type: wer |
|
value: 8.6074 |
|
- name: Test CER using LM |
|
type: cer |
|
value: 2.4147 |
|
--- |
|
|
|
<!-- 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-large-xls-r-300m-ia |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1452 |
|
- Wer: 0.1253 |
|
|
|
## Training Procedure |
|
|
|
Training is conducted in Google Colab, the training notebook provided in the repo |
|
|
|
## Training and evaluation data |
|
|
|
Language Model Created from texts from processed sentence in train + validation split of dataset (common voice 8.0 for Interlingua) |
|
Evaluation is conducted in Notebook, you can see within the repo "notebook_evaluation_wav2vec2_ia.ipynb" |
|
|
|
Test WER without LM |
|
wer = 20.1776 % |
|
cer = 4.7205 % |
|
|
|
Test WER using |
|
wer = 8.6074 % |
|
cer = 2.4147 % |
|
|
|
evaluation using eval.py |
|
``` |
|
huggingface-cli login #login to huggingface for getting auth token to access the common voice v8 |
|
#running with LM |
|
python eval.py --model_id ayameRushia/wav2vec2-large-xls-r-300m-ia --dataset mozilla-foundation/common_voice_8_0 --config ia --split test |
|
|
|
# running without LM |
|
python eval.py --model_id ayameRushia/wav2vec2-large-xls-r-300m-ia --dataset mozilla-foundation/common_voice_8_0 --config ia --split test --greedy |
|
``` |
|
|
|
### Training hyperparameters |
|
|
|
The following hyperparameters were used during training: |
|
- learning_rate: 3e-05 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 4 |
|
- 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: 400 |
|
- num_epochs: 30 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 7.432 | 1.87 | 400 | 2.9636 | 1.0 | |
|
| 2.6922 | 3.74 | 800 | 2.2111 | 0.9977 | |
|
| 1.2581 | 5.61 | 1200 | 0.4864 | 0.4028 | |
|
| 0.6232 | 7.48 | 1600 | 0.2807 | 0.2413 | |
|
| 0.4479 | 9.35 | 2000 | 0.2219 | 0.1885 | |
|
| 0.3654 | 11.21 | 2400 | 0.1886 | 0.1606 | |
|
| 0.323 | 13.08 | 2800 | 0.1716 | 0.1444 | |
|
| 0.2935 | 14.95 | 3200 | 0.1687 | 0.1443 | |
|
| 0.2707 | 16.82 | 3600 | 0.1632 | 0.1382 | |
|
| 0.2559 | 18.69 | 4000 | 0.1507 | 0.1337 | |
|
| 0.2433 | 20.56 | 4400 | 0.1572 | 0.1358 | |
|
| 0.2338 | 22.43 | 4800 | 0.1489 | 0.1305 | |
|
| 0.2258 | 24.3 | 5200 | 0.1485 | 0.1278 | |
|
| 0.2218 | 26.17 | 5600 | 0.1470 | 0.1272 | |
|
| 0.2169 | 28.04 | 6000 | 0.1470 | 0.1270 | |
|
| 0.2117 | 29.91 | 6400 | 0.1452 | 0.1253 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.17.0.dev0 |
|
- Pytorch 1.10.0+cu111 |
|
- Datasets 1.18.3 |
|
- Tokenizers 0.11.0 |
|
|
