File size: 6,897 Bytes
f5abee7 2272c97 f5abee7 2272c97 2f55395 f5abee7 2272c97 f5abee7 2272c97 2f55395 2272c97 2f55395 4a25a64 2f55395 f5abee7 2272c97 f5abee7 4a25a64 f5abee7 4a25a64 f5abee7 4a25a64 f5abee7 4a25a64 f5abee7 4a25a64 f5abee7 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 |
---
language:
- br
license: apache-2.0
tags:
- generated_from_trainer
- robust-speech-event
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_8_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-br-d10
results:
- task:
type: automatic-speech-recognition
name: Speech Recognition
dataset:
type: mozilla-foundation/common_voice_8_0
name: Common Voice 8
args: br
metrics:
- type: wer
value: 0.5230357484228637
name: Test WER
- name: Test CER
type: cer
value: 0.1880661144228536
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Dev Data
type: speech-recognition-community-v2/dev_data
args: br
metrics:
- name: Test WER
type: wer
value: NA
- name: Test CER
type: cer
value: NA
---
<!-- 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-br-d10
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 - BR dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1382
- Wer: 0.4895
### 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-br-d10 --dataset mozilla-foundation/common_voice_8_0 --config br --split test --log_outputs
2. To evaluate on speech-recognition-community-v2/dev_data
Breton language isn't available in speech-recognition-community-v2/dev_data
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0004
- 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: 800
- num_epochs: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 13.611 | 0.68 | 100 | 5.8492 | 1.0 |
| 3.8176 | 1.35 | 200 | 3.2181 | 1.0 |
| 3.0457 | 2.03 | 300 | 3.0902 | 1.0 |
| 2.2632 | 2.7 | 400 | 1.4882 | 0.9426 |
| 1.1965 | 3.38 | 500 | 1.1396 | 0.7950 |
| 0.984 | 4.05 | 600 | 1.0216 | 0.7583 |
| 0.8036 | 4.73 | 700 | 1.0258 | 0.7202 |
| 0.7061 | 5.41 | 800 | 0.9710 | 0.6820 |
| 0.689 | 6.08 | 900 | 0.9731 | 0.6488 |
| 0.6063 | 6.76 | 1000 | 0.9442 | 0.6569 |
| 0.5215 | 7.43 | 1100 | 1.0221 | 0.6671 |
| 0.4965 | 8.11 | 1200 | 0.9266 | 0.6181 |
| 0.4321 | 8.78 | 1300 | 0.9050 | 0.5991 |
| 0.3762 | 9.46 | 1400 | 0.9801 | 0.6134 |
| 0.3747 | 10.14 | 1500 | 0.9210 | 0.5747 |
| 0.3554 | 10.81 | 1600 | 0.9720 | 0.6051 |
| 0.3148 | 11.49 | 1700 | 0.9672 | 0.6099 |
| 0.3176 | 12.16 | 1800 | 1.0120 | 0.5966 |
| 0.2915 | 12.84 | 1900 | 0.9490 | 0.5653 |
| 0.2696 | 13.51 | 2000 | 0.9394 | 0.5819 |
| 0.2569 | 14.19 | 2100 | 1.0197 | 0.5667 |
| 0.2395 | 14.86 | 2200 | 0.9771 | 0.5608 |
| 0.2367 | 15.54 | 2300 | 1.0516 | 0.5678 |
| 0.2153 | 16.22 | 2400 | 1.0097 | 0.5679 |
| 0.2092 | 16.89 | 2500 | 1.0143 | 0.5430 |
| 0.2046 | 17.57 | 2600 | 1.0884 | 0.5631 |
| 0.1937 | 18.24 | 2700 | 1.0113 | 0.5648 |
| 0.1752 | 18.92 | 2800 | 1.0056 | 0.5470 |
| 0.164 | 19.59 | 2900 | 1.0340 | 0.5508 |
| 0.1723 | 20.27 | 3000 | 1.0743 | 0.5615 |
| 0.1535 | 20.95 | 3100 | 1.0495 | 0.5465 |
| 0.1432 | 21.62 | 3200 | 1.0390 | 0.5333 |
| 0.1561 | 22.3 | 3300 | 1.0798 | 0.5590 |
| 0.1384 | 22.97 | 3400 | 1.1716 | 0.5449 |
| 0.1359 | 23.65 | 3500 | 1.1154 | 0.5420 |
| 0.1356 | 24.32 | 3600 | 1.0883 | 0.5387 |
| 0.1355 | 25.0 | 3700 | 1.1114 | 0.5504 |
| 0.1158 | 25.68 | 3800 | 1.1171 | 0.5388 |
| 0.1166 | 26.35 | 3900 | 1.1335 | 0.5403 |
| 0.1165 | 27.03 | 4000 | 1.1374 | 0.5248 |
| 0.1064 | 27.7 | 4100 | 1.0336 | 0.5298 |
| 0.0987 | 28.38 | 4200 | 1.0407 | 0.5216 |
| 0.104 | 29.05 | 4300 | 1.1012 | 0.5350 |
| 0.0894 | 29.73 | 4400 | 1.1016 | 0.5310 |
| 0.0912 | 30.41 | 4500 | 1.1383 | 0.5302 |
| 0.0972 | 31.08 | 4600 | 1.0851 | 0.5214 |
| 0.0832 | 31.76 | 4700 | 1.1705 | 0.5311 |
| 0.0859 | 32.43 | 4800 | 1.0750 | 0.5192 |
| 0.0811 | 33.11 | 4900 | 1.0900 | 0.5180 |
| 0.0825 | 33.78 | 5000 | 1.1271 | 0.5196 |
| 0.07 | 34.46 | 5100 | 1.1289 | 0.5141 |
| 0.0689 | 35.14 | 5200 | 1.0960 | 0.5101 |
| 0.068 | 35.81 | 5300 | 1.1377 | 0.5050 |
| 0.0776 | 36.49 | 5400 | 1.0880 | 0.5194 |
| 0.0642 | 37.16 | 5500 | 1.1027 | 0.5076 |
| 0.0607 | 37.84 | 5600 | 1.1293 | 0.5119 |
| 0.0607 | 38.51 | 5700 | 1.1229 | 0.5103 |
| 0.0545 | 39.19 | 5800 | 1.1168 | 0.5103 |
| 0.0562 | 39.86 | 5900 | 1.1206 | 0.5073 |
| 0.0484 | 40.54 | 6000 | 1.1710 | 0.5019 |
| 0.0499 | 41.22 | 6100 | 1.1511 | 0.5100 |
| 0.0455 | 41.89 | 6200 | 1.1488 | 0.5009 |
| 0.0475 | 42.57 | 6300 | 1.1196 | 0.4944 |
| 0.0413 | 43.24 | 6400 | 1.1654 | 0.4996 |
| 0.0389 | 43.92 | 6500 | 1.0961 | 0.4930 |
| 0.0428 | 44.59 | 6600 | 1.0955 | 0.4938 |
| 0.039 | 45.27 | 6700 | 1.1323 | 0.4955 |
| 0.0352 | 45.95 | 6800 | 1.1040 | 0.4930 |
| 0.0334 | 46.62 | 6900 | 1.1382 | 0.4942 |
| 0.0338 | 47.3 | 7000 | 1.1264 | 0.4911 |
| 0.0307 | 47.97 | 7100 | 1.1216 | 0.4881 |
| 0.0286 | 48.65 | 7200 | 1.1459 | 0.4894 |
| 0.0348 | 49.32 | 7300 | 1.1419 | 0.4906 |
| 0.0329 | 50.0 | 7400 | 1.1382 | 0.4895 |
### Framework versions
- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0
|