README.md

metadata

base_model: hf-internal-testing/tiny-albert
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: results
    results: []

results

This model is a fine-tuned version of hf-internal-testing/tiny-albert on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.1315
• Accuracy: 0.96

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: 0.001
• train_batch_size: 24
• eval_batch_size: 24
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 25.0
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6937	0.1	25	0.6927	0.5115
0.6911	0.2	50	0.6770	0.613
0.4988	0.3	75	0.3574	0.886
0.2604	0.4	100	0.1720	0.9525
0.1758	0.5	125	0.1787	0.9435
0.1964	0.6	150	0.1327	0.9615
0.1637	0.7	175	0.1269	0.9635
0.1453	0.8	200	0.1538	0.9565
0.1563	0.9	225	0.1508	0.9575
0.1657	1.0	250	0.1315	0.96

Framework versions

• Transformers 4.40.0
• Pytorch 2.2.1+cu121
• Datasets 2.19.0
• Tokenizers 0.19.1