File size: 2,269 Bytes
40fec30 f2d23d5 40fec30 f2d23d5 40fec30 f2d23d5 40fec30 37e702b 40fec30 37e702b 40fec30 37e702b 40fec30 f2d23d5 40fec30 |
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 |
---
tags:
- generated_from_trainer
datasets:
- evanarlian/common_voice_11_0_id_filtered
metrics:
- wer
model-index:
- name: wav2vec2-xls-r-113m-id
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: evanarlian/common_voice_11_0_id_filtered
type: evanarlian/common_voice_11_0_id_filtered
metrics:
- name: Wer
type: wer
value: 0.6403468314731113
---
<!-- 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-xls-r-113m-id
This model is a fine-tuned version of [evanarlian/distil-wav2vec2-xls-r-113m-id](https://huggingface.co/evanarlian/distil-wav2vec2-xls-r-113m-id) on the evanarlian/common_voice_11_0_id_filtered dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5214
- Wer: 0.6403
## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.3
- num_epochs: 5.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.8452 | 0.61 | 1000 | 2.8065 | 1.0 |
| 1.3277 | 1.22 | 2000 | 1.0774 | 0.9330 |
| 1.025 | 1.84 | 3000 | 0.8000 | 0.8474 |
| 0.8497 | 2.45 | 4000 | 0.6812 | 0.7669 |
| 0.7678 | 3.06 | 5000 | 0.6125 | 0.7186 |
| 0.6886 | 3.67 | 6000 | 0.5758 | 0.6812 |
| 0.6318 | 4.29 | 7000 | 0.5420 | 0.6570 |
| 0.6086 | 4.9 | 8000 | 0.5214 | 0.6403 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.7.1
- Tokenizers 0.13.1
|