MiniLM_uncased_classification_tools_classifier-only_fr

This model is a fine-tuned version of microsoft/MiniLM-L12-H384-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 2.0829
• Accuracy: 0.075
• Learning Rate: 0.0001

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: 24
• eval_batch_size: 192
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 60

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Rate
No log	1.0	7	2.0791	0.125	0.0001
No log	2.0	14	2.0797	0.075	0.0001
No log	3.0	21	2.0799	0.075	0.0001
No log	4.0	28	2.0804	0.075	0.0001
No log	5.0	35	2.0808	0.075	0.0001
No log	6.0	42	2.0813	0.075	9e-05
No log	7.0	49	2.0818	0.075	0.0001
No log	8.0	56	2.0820	0.075	0.0001
No log	9.0	63	2.0822	0.075	0.0001
No log	10.0	70	2.0827	0.075	0.0001
No log	11.0	77	2.0829	0.075	0.0001

Framework versions

• Transformers 4.34.0
• Pytorch 2.0.1+cu117
• Datasets 2.14.5
• Tokenizers 0.14.1