metadata
library_name: transformers
tags: []
Model Card for Model ID
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]