update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,72 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
base_model: ''
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
metrics:
|
| 6 |
+
- rouge
|
| 7 |
+
model-index:
|
| 8 |
+
- name: wav2GPT2Musicfreeze
|
| 9 |
+
results: []
|
| 10 |
+
---
|
| 11 |
+
|
| 12 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 13 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 14 |
+
|
| 15 |
+
# wav2GPT2Musicfreeze
|
| 16 |
+
|
| 17 |
+
This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
|
| 18 |
+
It achieves the following results on the evaluation set:
|
| 19 |
+
- Loss: 1.0685
|
| 20 |
+
- Rouge1: 32.5473
|
| 21 |
+
- Rouge2: 9.2754
|
| 22 |
+
- Rougel: 23.52
|
| 23 |
+
- Rougelsum: 23.5525
|
| 24 |
+
- Gen Len: 74.0
|
| 25 |
+
|
| 26 |
+
## Model description
|
| 27 |
+
|
| 28 |
+
More information needed
|
| 29 |
+
|
| 30 |
+
## Intended uses & limitations
|
| 31 |
+
|
| 32 |
+
More information needed
|
| 33 |
+
|
| 34 |
+
## Training and evaluation data
|
| 35 |
+
|
| 36 |
+
More information needed
|
| 37 |
+
|
| 38 |
+
## Training procedure
|
| 39 |
+
|
| 40 |
+
### Training hyperparameters
|
| 41 |
+
|
| 42 |
+
The following hyperparameters were used during training:
|
| 43 |
+
- learning_rate: 5e-05
|
| 44 |
+
- train_batch_size: 4
|
| 45 |
+
- eval_batch_size: 4
|
| 46 |
+
- seed: 42
|
| 47 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 48 |
+
- lr_scheduler_type: linear
|
| 49 |
+
- num_epochs: 10
|
| 50 |
+
|
| 51 |
+
### Training results
|
| 52 |
+
|
| 53 |
+
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|
| 54 |
+
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
|
| 55 |
+
| 2.2767 | 1.0 | 1361 | 1.8699 | 31.5702 | 8.644 | 23.435 | 23.5065 | 54.0 |
|
| 56 |
+
| 1.9325 | 2.0 | 2722 | 1.6511 | 29.4728 | 8.9646 | 21.6881 | 21.6896 | 87.0 |
|
| 57 |
+
| 1.7731 | 3.0 | 4083 | 1.5085 | 29.7153 | 8.7535 | 21.8973 | 21.9541 | 85.0 |
|
| 58 |
+
| 1.638 | 4.0 | 5444 | 1.4016 | 32.9074 | 7.9981 | 23.745 | 23.7152 | 59.0 |
|
| 59 |
+
| 1.5524 | 5.0 | 6805 | 1.2975 | 32.8051 | 9.6371 | 23.658 | 23.6868 | 74.0 |
|
| 60 |
+
| 1.4795 | 6.0 | 8166 | 1.2239 | 27.9746 | 7.7738 | 20.7341 | 20.6989 | 50.0 |
|
| 61 |
+
| 1.4163 | 7.0 | 9527 | 1.1602 | 29.1471 | 7.3243 | 22.2569 | 22.253 | 57.0 |
|
| 62 |
+
| 1.3457 | 8.0 | 10888 | 1.1083 | 33.2668 | 9.4555 | 23.5864 | 23.6329 | 78.0 |
|
| 63 |
+
| 1.3106 | 9.0 | 12249 | 1.0809 | 32.5473 | 9.2754 | 23.52 | 23.5525 | 74.0 |
|
| 64 |
+
| 1.2819 | 10.0 | 13610 | 1.0685 | 32.5473 | 9.2754 | 23.52 | 23.5525 | 74.0 |
|
| 65 |
+
|
| 66 |
+
|
| 67 |
+
### Framework versions
|
| 68 |
+
|
| 69 |
+
- Transformers 4.31.0
|
| 70 |
+
- Pytorch 2.0.1+cu117
|
| 71 |
+
- Datasets 2.14.2
|
| 72 |
+
- Tokenizers 0.13.3
|