distilrubert-2ndfinetune-epru – AI Model by mmillet | AlphaNeural AI

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mmillet/
distilrubert-2ndfinetune-epru

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text-classification

generated_from_trainer

autotrain_compatible

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distilrubert-2ndfinetune-epru

This model is a fine-tuned version of mmillet/distilrubert-tiny-cased-conversational-v1_best_finetuned_emotion_experiment_augmented_anger_fear on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.3531
Accuracy: 0.9054
F1: 0.9034
Precision: 0.9074
Recall: 0.9054

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: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.4716	1.0	11	0.2851	0.8986	0.8945	0.9029	0.8986
0.2842	2.0	22	0.3041	0.8851	0.8796	0.8816	0.8851
0.167	3.0	33	0.2996	0.8986	0.8914	0.8997	0.8986
0.1527	4.0	44	0.2443	0.9189	0.9163	0.9222	0.9189
0.0926	5.0	55	0.2777	0.9054	0.9016	0.9059	0.9054
0.0897	6.0	66	0.3081	0.9122	0.9080	0.9147	0.9122
0.0438	7.0	77	0.3332	0.8986	0.8952	0.8993	0.8986
0.0433	8.0	88	0.3480	0.8851	0.8859	0.8896	0.8851
0.0398	9.0	99	0.3531	0.9054	0.9034	0.9074	0.9054

Framework versions

Transformers 4.19.3
Pytorch 1.11.0+cu113
Datasets 2.2.2
Tokenizers 0.12.1