Model save
Browse files
README.md
ADDED
|
@@ -0,0 +1,88 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
base_model: facebook/wav2vec2-large-lv60
|
| 4 |
+
tags:
|
| 5 |
+
- generated_from_trainer
|
| 6 |
+
datasets:
|
| 7 |
+
- ami
|
| 8 |
+
metrics:
|
| 9 |
+
- wer
|
| 10 |
+
model-index:
|
| 11 |
+
- name: wav2vec2-large-ami-fine-tuned
|
| 12 |
+
results:
|
| 13 |
+
- task:
|
| 14 |
+
name: Automatic Speech Recognition
|
| 15 |
+
type: automatic-speech-recognition
|
| 16 |
+
dataset:
|
| 17 |
+
name: ami
|
| 18 |
+
type: ami
|
| 19 |
+
config: ihm
|
| 20 |
+
split: None
|
| 21 |
+
args: ihm
|
| 22 |
+
metrics:
|
| 23 |
+
- name: Wer
|
| 24 |
+
type: wer
|
| 25 |
+
value: 0.8711243810697664
|
| 26 |
+
---
|
| 27 |
+
|
| 28 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 29 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 30 |
+
|
| 31 |
+
# wav2vec2-large-ami-fine-tuned
|
| 32 |
+
|
| 33 |
+
This model is a fine-tuned version of [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) on the ami dataset.
|
| 34 |
+
It achieves the following results on the evaluation set:
|
| 35 |
+
- Loss: 0.9830
|
| 36 |
+
- Wer: 0.8711
|
| 37 |
+
|
| 38 |
+
## Model description
|
| 39 |
+
|
| 40 |
+
More information needed
|
| 41 |
+
|
| 42 |
+
## Intended uses & limitations
|
| 43 |
+
|
| 44 |
+
More information needed
|
| 45 |
+
|
| 46 |
+
## Training and evaluation data
|
| 47 |
+
|
| 48 |
+
More information needed
|
| 49 |
+
|
| 50 |
+
## Training procedure
|
| 51 |
+
|
| 52 |
+
### Training hyperparameters
|
| 53 |
+
|
| 54 |
+
The following hyperparameters were used during training:
|
| 55 |
+
- learning_rate: 0.00014
|
| 56 |
+
- train_batch_size: 16
|
| 57 |
+
- eval_batch_size: 16
|
| 58 |
+
- seed: 42
|
| 59 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 60 |
+
- lr_scheduler_type: linear
|
| 61 |
+
- lr_scheduler_warmup_steps: 1000
|
| 62 |
+
- num_epochs: 2.0
|
| 63 |
+
- mixed_precision_training: Native AMP
|
| 64 |
+
|
| 65 |
+
### Training results
|
| 66 |
+
|
| 67 |
+
| Training Loss | Epoch | Step | Validation Loss | Wer |
|
| 68 |
+
|:-------------:|:------:|:-----:|:---------------:|:------:|
|
| 69 |
+
| 1.5455 | 0.1565 | 1000 | 1.3698 | 0.8373 |
|
| 70 |
+
| 1.3019 | 0.3131 | 2000 | 0.7275 | 0.4146 |
|
| 71 |
+
| 0.9922 | 0.4696 | 3000 | 0.6047 | 0.3663 |
|
| 72 |
+
| 0.5129 | 0.6262 | 4000 | 0.5773 | 0.3658 |
|
| 73 |
+
| 0.85 | 0.7827 | 5000 | 0.5387 | 0.3538 |
|
| 74 |
+
| 1.4588 | 0.9393 | 6000 | 0.5581 | 0.3326 |
|
| 75 |
+
| 0.2646 | 1.0958 | 7000 | 0.5216 | 0.3294 |
|
| 76 |
+
| 0.1923 | 1.2523 | 8000 | 0.4975 | 0.3159 |
|
| 77 |
+
| 0.2897 | 1.4089 | 9000 | 0.4757 | 0.3066 |
|
| 78 |
+
| 0.1536 | 1.5654 | 10000 | 0.4784 | 0.3066 |
|
| 79 |
+
| 0.3964 | 1.7220 | 11000 | 0.4899 | 0.3097 |
|
| 80 |
+
| 1.1026 | 1.8785 | 12000 | 0.9830 | 0.8711 |
|
| 81 |
+
|
| 82 |
+
|
| 83 |
+
### Framework versions
|
| 84 |
+
|
| 85 |
+
- Transformers 4.42.0.dev0
|
| 86 |
+
- Pytorch 2.3.0a0+gitcd033a1
|
| 87 |
+
- Datasets 2.19.1
|
| 88 |
+
- Tokenizers 0.19.1
|