wav2GPT2MusiSD3100 – AI Model by nacielo | AlphaNeural AI

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nacielo/
wav2GPT2MusiSD3100

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speech-encoder-decoder

automatic-speech-recognition

generated_from_trainer

endpoints_compatible

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wav2GPT2MusiSD3100

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

Loss: 1.4092
Rouge1: 15.6142
Rouge2: 2.2075
Rougel: 14.8541
Rougelsum: 14.8888
Gen Len: 60.0

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: 1e-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
1.9569	1.0	959	1.7932	19.6635	2.3177	17.8258	17.8164	57.0
1.7035	2.0	1918	1.6795	18.4799	2.3155	16.3977	16.4296	63.0
1.6267	3.0	2877	1.6036	21.2993	2.9167	19.1184	19.1044	61.0
1.5669	4.0	3836	1.5429	16.6273	2.141	15.4121	15.4484	60.0
1.5373	5.0	4795	1.4901	15.6142	2.2075	14.8541	14.8888	60.0
1.5333	6.0	5754	1.4583	14.3844	2.1564	13.524	13.5429	58.0
1.5303	7.0	6713	1.4323	15.6142	2.2075	14.8541	14.8888	60.0
1.5337	8.0	7672	1.4156	15.6142	2.2075	14.8541	14.8888	60.0
1.5518	9.0	8631	1.4099	15.6142	2.2075	14.8541	14.8888	60.0
1.5764	10.0	9590	1.4092	15.6142	2.2075	14.8541	14.8888	60.0

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu117
Datasets 2.14.2
Tokenizers 0.13.3