metadata

tags:
  - generated_from_keras_callback
model-index:
  - name: distilbert_new2_0040
    results: []

distilbert_new2_0040

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: 0.9702
Validation Loss: 0.9482
Epoch: 39

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

Framework versions

Transformers 4.20.1
TensorFlow 2.8.2
Datasets 2.3.2
Tokenizers 0.12.1