distilbert-base-uncased-finetuned-cnn – AI Model by SmartPy | AlphaNeural AI

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distilbert-base-uncased-finetuned-cnn

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distilbert-base-uncased-finetuned-cnn

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.2647

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: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
2.2811	1.0	157	2.3283
2.3086	2.0	314	2.3172
2.3472	3.0	471	2.3033
2.3608	4.0	628	2.2989
2.3494	5.0	785	2.2975
2.3217	6.0	942	2.2701
2.3087	7.0	1099	2.2545
2.291	8.0	1256	2.2376
2.2983	9.0	1413	2.2653
2.2892	10.0	1570	2.2647

Framework versions

Transformers 4.20.1
Pytorch 1.11.0
Datasets 2.1.0
Tokenizers 0.12.1