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---
language:
- bg
license: apache-2.0
tags:
- automatic-speech-recognition
- bg
- generated_from_trainer
- hf-asr-leaderboard
- model_for_talk
- mozilla-foundation/common_voice_8_0
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: wav2vec2-large-xls-r-300m-bg-v1
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 8
type: mozilla-foundation/common_voice_8_0
args: bg
metrics:
- name: Test WER
type: wer
value: 0.4709579127785184
- name: Test CER
type: cer
value: 0.10205125354383235
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Dev Data
type: speech-recognition-community-v2/dev_data
args: bg
metrics:
- name: Test WER
type: wer
value: 0.7053128872366791
- name: Test CER
type: cer
value: 0.210804311998487
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Test Data
type: speech-recognition-community-v2/eval_data
args: bg
metrics:
- name: Test WER
type: wer
value: 72.6
---
<!-- 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. -->
#
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - BG dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5197
- Wer: 0.4689
### Evaluation Commands
1. To evaluate on mozilla-foundation/common_voice_8_0 with test split
python eval.py --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-bg-v1 --dataset mozilla-foundation/common_voice_8_0 --config bg --split test --log_outputs
2. To evaluate on speech-recognition-community-v2/dev_data
python eval.py --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-bg-v1 --dataset speech-recognition-community-v2/dev_data --config bg --split validation --chunk_length_s 10 --stride_length_s 1
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 7e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 50.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.3711 | 2.61 | 300 | 4.3122 | 1.0 |
| 3.1653 | 5.22 | 600 | 3.1156 | 1.0 |
| 2.8904 | 7.83 | 900 | 2.8421 | 0.9918 |
| 0.9207 | 10.43 | 1200 | 0.9895 | 0.8689 |
| 0.6384 | 13.04 | 1500 | 0.6994 | 0.7700 |
| 0.5215 | 15.65 | 1800 | 0.5628 | 0.6443 |
| 0.4573 | 18.26 | 2100 | 0.5316 | 0.6174 |
| 0.3875 | 20.87 | 2400 | 0.4932 | 0.5779 |
| 0.3562 | 23.48 | 2700 | 0.4972 | 0.5475 |
| 0.3218 | 26.09 | 3000 | 0.4895 | 0.5219 |
| 0.2954 | 28.7 | 3300 | 0.5226 | 0.5192 |
| 0.287 | 31.3 | 3600 | 0.4957 | 0.5146 |
| 0.2587 | 33.91 | 3900 | 0.4944 | 0.4893 |
| 0.2496 | 36.52 | 4200 | 0.4976 | 0.4895 |
| 0.2365 | 39.13 | 4500 | 0.5185 | 0.4819 |
| 0.2264 | 41.74 | 4800 | 0.5152 | 0.4776 |
| 0.2224 | 44.35 | 5100 | 0.5031 | 0.4746 |
| 0.2096 | 46.96 | 5400 | 0.5062 | 0.4708 |
| 0.2038 | 49.57 | 5700 | 0.5217 | 0.4698 |
### Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0
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