File size: 2,626 Bytes
5a62cc8 055a81a f5c5dca 5a62cc8 c19bb13 5a62cc8 ead065f 055a81a ead065f 055a81a 5a62cc8 |
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 |
---
language:
- bas
license: apache-2.0
tags:
- automatic-speech-recognition
- generated_from_trainer
- hf-asr-leaderboard
- mozilla-foundation/common_voice_7_0
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: XLS-R-300M - Basaa
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 7
type: mozilla-foundation/common_voice_7_0
args: bas
metrics:
- name: Test WER
type: wer
value: 104.08
- name: Test CER
type: cer
value: 228.48
---
<!-- 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-basaa
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_7_0 - BAS dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5975
- Wer: 0.4981
## 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: 7e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 200.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 2.9287 | 15.62 | 500 | 2.8774 | 1.0 |
| 1.1182 | 31.25 | 1000 | 0.6248 | 0.7131 |
| 0.8329 | 46.88 | 1500 | 0.5573 | 0.5792 |
| 0.7109 | 62.5 | 2000 | 0.5420 | 0.5683 |
| 0.6295 | 78.12 | 2500 | 0.5166 | 0.5395 |
| 0.5715 | 93.75 | 3000 | 0.5487 | 0.5629 |
| 0.5016 | 109.38 | 3500 | 0.5370 | 0.5471 |
| 0.4661 | 125.0 | 4000 | 0.5621 | 0.5395 |
| 0.423 | 140.62 | 4500 | 0.5658 | 0.5248 |
| 0.3793 | 156.25 | 5000 | 0.5921 | 0.4981 |
| 0.3651 | 171.88 | 5500 | 0.5987 | 0.4888 |
| 0.3351 | 187.5 | 6000 | 0.6017 | 0.4948 |
### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0
|