wav2GPT2MusiSD3100 / README.md
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metadata
base_model: ''
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: wav2GPT2MusiSD3100
    results: []

wav2GPT2MusiSD3100

This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.4543
  • Rouge1: 14.9678
  • Rouge2: 2.1649
  • Rougel: 14.4205
  • Rougelsum: 14.4408
  • Gen Len: 64.0

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: 5e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
2.7082 1.0 959 2.5321 18.3219 2.1594 17.0253 17.0044 82.0
2.2926 2.0 1918 2.3019 17.7317 2.1985 16.3236 16.3132 71.0
2.1349 3.0 2877 2.1208 21.6818 2.6244 19.1082 19.0883 58.0
1.9939 4.0 3836 1.9543 19.6238 2.7829 17.8229 17.7944 72.0
1.8933 5.0 4795 1.8055 17.2105 2.0041 16.7053 16.766 46.0
1.8068 6.0 5754 1.6966 14.8562 2.0662 14.4525 14.4841 64.0
1.7375 7.0 6713 1.5950 15.0644 2.1461 14.7203 14.7665 65.0
1.6704 8.0 7672 1.5214 14.9678 2.1649 14.4205 14.4408 64.0
1.6254 9.0 8631 1.4738 14.9678 2.1649 14.4205 14.4408 64.0
1.5941 10.0 9590 1.4543 14.9678 2.1649 14.4205 14.4408 64.0

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.2
  • Tokenizers 0.13.3