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ASR_fassy – AI Model by fastinom | AlphaNeural AI | AlphaNeural AI
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fastinom
/
ASR_fassy
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transformers
tensorboard
safetensors
wav2vec2
automatic-speech-recognition
1910.09700
endpoints_compatible
us
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Model Details
Model Description
This is the model card of a 🤗 transformers model that has been pushed on the Hub.
Developed by:
[Fastino Mateteva]
Model type:
[Transformer model]
Language(s) (NLP):
[Shona]
License:
[]
How to Get Started with the Model
Use the code below to get started with the model.
Running the model
Training Details
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 5e-4
per_device_train_batch_size=4
eval_batch_size: 2
evaluation_strategy="steps"
gradient_checkpointing=True
gradient_accumulation_steps: 4
total_train_batch_size: 16
num_train_epochs=3
save_total_limit=1
fp16=True
save_steps=400
eval_steps=200
logging_steps=200
push_to_hub=True
Training results
Training Loss
WER
Step
Validation Loss
6.427
1.00
200
4.1518
3.7979
1.00
400
3.8410
3.6924
1.00
600
3.4249
0.8357
0.26
800
0.2396
0.1528
0.24
1000
0.2155
0.1415
0.24
1200
0.2036
0.1278
0.24
1400
0.2028
Environmental Impact
Carbon emissions can be estimated using the
Machine Learning Impact calculator
presented in
Lacoste et al. (2019)
.
Hardware Type:
[T4 GPU]
Hours used:
[3]
Cloud Provider:
[Google Colab]
Technical Specifications [optional]
Model Architecture and Objective
[More Information Needed]
Compute Infrastructure
[More Information Needed]
Hardware
[More Information Needed]
Software
[More Information Needed]
Model Card Authors [optional]
[Fastino Mateteva]
Model Card Contact
[
fastinomateteva@gmail.com
]
