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finetune_wav2vec2_base_six_1000 – AI Model by ImanN1 | AlphaNeural AI
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finetune_wav2vec2_base_six_1000
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transformers
tensorboard
safetensors
wav2vec2
automatic-speech-recognition
generated_from_trainer
facebook/wav2vec2-base
finetune
apache-2.0
endpoints_compatible
us
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finetune_wav2vec2_base_six_1000
This model is a fine-tuned version of
facebook/wav2vec2-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.3205
Wer: 64.2346
Cer: 28.5983
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: 0.0001
train_batch_size: 32
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 2000
training_steps: 4500
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
Cer
3.3064
18.5185
1000
1.2395
61.2364
27.0612
0.4719
37.0370
2000
1.1869
43.9153
20.5975
0.1675
55.5556
3000
1.2026
41.3812
19.3565
0.0898
74.0741
4000
1.2615
39.3484
18.3855
Framework versions
Transformers 4.40.2
Pytorch 1.12.1+cu116
Datasets 2.19.1
Tokenizers 0.19.1
