File size: 4,166 Bytes
619707e 6a75085 619707e 6a75085 076b731 6a75085 619707e 8699225 619707e 6a75085 4d1fc3e 6a75085 4d1fc3e f49dff6 4d1fc3e 619707e 84bee6f 619707e f49dff6 619707e f49dff6 619707e f49dff6 619707e f49dff6 619707e f49dff6 619707e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 |
---
language:
- bg
license: apache-2.0
tags:
- automatic-speech-recognition
- bg
- generated_from_trainer
- hf-asr-leaderboard
- 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-d2
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: 0.28775471338792613
- name: Test CER
type: cer
value: 0.06861971204625049
- 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: 0.49783147459727384
- name: Test CER
type: cer
value: 0.1591062599627158
- 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: 51.25
---
<!-- 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-bg-d2
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: 0.3421
- Wer: 0.2860
### 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-d2 --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-d2 --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: 0.00025
- 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: 700
- num_epochs: 35
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 6.8791 | 1.74 | 200 | 3.1902 | 1.0 |
| 3.0441 | 3.48 | 400 | 2.8098 | 0.9864 |
| 1.1499 | 5.22 | 600 | 0.4668 | 0.5014 |
| 0.4968 | 6.96 | 800 | 0.4162 | 0.4472 |
| 0.3553 | 8.7 | 1000 | 0.3580 | 0.3777 |
| 0.3027 | 10.43 | 1200 | 0.3422 | 0.3506 |
| 0.2562 | 12.17 | 1400 | 0.3556 | 0.3639 |
| 0.2272 | 13.91 | 1600 | 0.3621 | 0.3583 |
| 0.2125 | 15.65 | 1800 | 0.3436 | 0.3358 |
| 0.1904 | 17.39 | 2000 | 0.3650 | 0.3545 |
| 0.1695 | 19.13 | 2200 | 0.3366 | 0.3241 |
| 0.1532 | 20.87 | 2400 | 0.3550 | 0.3311 |
| 0.1453 | 22.61 | 2600 | 0.3582 | 0.3131 |
| 0.1359 | 24.35 | 2800 | 0.3524 | 0.3084 |
| 0.1233 | 26.09 | 3000 | 0.3503 | 0.2973 |
| 0.1114 | 27.83 | 3200 | 0.3434 | 0.2946 |
| 0.1051 | 29.57 | 3400 | 0.3474 | 0.2956 |
| 0.0965 | 31.3 | 3600 | 0.3426 | 0.2907 |
| 0.0923 | 33.04 | 3800 | 0.3478 | 0.2894 |
| 0.0894 | 34.78 | 4000 | 0.3421 | 0.2860 |
### Framework versions
- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0
|