distilbert_new2_0060

This model is a fine-tuned version of [/content/drive/MyDrive/Colab Notebooks/oscar/trybackup_distilbert/new_backup_0105105](https://huggingface.co//content/drive/MyDrive/Colab Notebooks/oscar/trybackup_distilbert/new_backup_0105105) on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.9522
• Validation Loss: 0.9345
• Epoch: 59

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:

• optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
• training_precision: float32

Training results

Train Loss	Validation Loss	Epoch
1.0180	0.9873	0
1.0163	0.9878	1
1.0145	0.9856	2
1.0139	0.9830	3
1.0122	0.9831	4
1.0118	0.9830	5
1.0094	0.9800	6
1.0075	0.9809	7
1.0066	0.9784	8
1.0062	0.9768	9
1.0032	0.9751	10
1.0023	0.9764	11
1.0008	0.9735	12
0.9994	0.9730	13
0.9986	0.9761	14
0.9975	0.9714	15
0.9953	0.9708	16
0.9941	0.9683	17
0.9933	0.9681	18
0.9920	0.9688	19
0.9907	0.9648	20
0.9897	0.9625	21
0.9890	0.9642	22
0.9873	0.9633	23
0.9867	0.9618	24
0.9857	0.9600	25
0.9839	0.9598	26
0.9827	0.9585	27
0.9821	0.9607	28
0.9809	0.9579	29
0.9803	0.9561	30
0.9786	0.9563	31
0.9774	0.9536	32
0.9766	0.9542	33
0.9756	0.9523	34
0.9743	0.9525	35
0.9730	0.9513	36
0.9721	0.9507	37
0.9715	0.9506	38
0.9702	0.9482	39
0.9694	0.9493	40
0.9689	0.9462	41
0.9673	0.9463	42
0.9669	0.9444	43
0.9659	0.9450	44
0.9643	0.9429	45
0.9625	0.9432	46
0.9625	0.9428	47
0.9609	0.9408	48
0.9598	0.9399	49
0.9596	0.9407	50
0.9590	0.9393	51
0.9580	0.9380	52
0.9562	0.9383	53
0.9558	0.9369	54
0.9543	0.9379	55
0.9545	0.9362	56
0.9534	0.9349	57
0.9523	0.9338	58
0.9522	0.9345	59

Framework versions

• Transformers 4.20.1
• TensorFlow 2.8.2
• Datasets 2.3.2
• Tokenizers 0.12.1