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wav2BertMusicfreezeTest – AI Model by nacielo | AlphaNeural AI
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wav2BertMusicfreezeTest
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transformers
pytorch
tensorboard
speech-encoder-decoder
automatic-speech-recognition
generated_from_trainer
endpoints_compatible
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wav2BertMusicfreezeTest
This model is a fine-tuned version of
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 6.6761
Rouge1: 16.6206
Rouge2: 0.9994
Rougel: 16.1142
Rougelsum: 16.1149
Gen Len: 95.3
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: 1e-06
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: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Rouge1
Rouge2
Rougel
Rougelsum
Gen Len
7.7819
1.0
1361
7.0617
15.5901
0.9705
15.3625
15.389
97.98
6.8553
2.0
2722
6.6761
16.6206
0.9994
16.1142
16.1149
95.3
Framework versions
Transformers 4.31.0
Pytorch 2.0.1+cu117
Datasets 2.14.2
Tokenizers 0.13.3
