File size: 2,340 Bytes
0bdecd6 8753f99 b3a5e81 8753f99 2d2aab7 0bdecd6 8753f99 0bdecd6 8753f99 0bdecd6 8753f99 2d2aab7 0bdecd6 8753f99 0bdecd6 b3a5e81 0bdecd6 8753f99 0bdecd6 8753f99 b3a5e81 8753f99 0bdecd6 8753f99 0bdecd6 2d2aab7 0bdecd6 8753f99 0bdecd6 8753f99 |
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 |
---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- ml-superb-subset
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-ssw
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: ml-superb-subset
type: ml-superb-subset
config: ssw
split: dev
args: ssw
metrics:
- name: Wer
type: wer
value: 0.9968847352024922
---
<!-- 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-ssw
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the ml-superb-subset dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4697
- Wer: 0.9969
## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 6.3138 | 1.0471 | 100 | 4.7003 | 1.0 |
| 3.1815 | 2.0942 | 200 | 3.1195 | 1.0 |
| 3.1618 | 3.1414 | 300 | 3.1440 | 1.0 |
| 3.068 | 4.1885 | 400 | 3.2146 | 1.0 |
| 3.0495 | 5.2356 | 500 | 3.0380 | 1.0 |
| 2.9972 | 6.2827 | 600 | 2.9489 | 1.0 |
| 2.6887 | 7.3298 | 700 | 2.5815 | 1.0 |
| 2.2022 | 8.3770 | 800 | 1.9518 | 1.0 |
| 1.6504 | 9.4241 | 900 | 1.4697 | 0.9969 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|