roberta-base-finetuned-intent – AI Model by zhiyil | AlphaNeural AI

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zhiyil/
roberta-base-finetuned-intent

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optimum_graphcore

text-classification

generated_from_trainer

snips_built_in_intents

autotrain_compatible

endpoints_compatible

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roberta-base-finetuned-intent

This model is a fine-tuned version of roberta-base on the snips_built_in_intents dataset. It achieves the following results on the evaluation set:

Loss: 0.2720
Accuracy: 0.9333

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: 2e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
distributed_type: IPU
gradient_accumulation_steps: 8
total_train_batch_size: 8
total_eval_batch_size: 5
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10
training precision: Mixed Precision

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.9568	1.0	37	1.7598	0.4333
1.2238	2.0	74	0.8130	0.7667
0.4536	3.0	111	0.4985	0.8
0.2478	4.0	148	0.3535	0.8667
0.0903	5.0	185	0.3110	0.8667
0.0849	6.0	222	0.2720	0.9333
0.0708	7.0	259	0.2742	0.8667
0.0796	8.0	296	0.2839	0.8667
0.0638	9.0	333	0.2949	0.8667
0.0566	10.0	370	0.2925	0.8667

Framework versions

Transformers 4.20.1
Pytorch 1.10.0+cpu
Datasets 2.7.1
Tokenizers 0.12.0