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PiotrNaspinski/
TrainingArg

Name: TrainingArg
Availability: InStock

safetensors

distilbert

generated_from_trainer

text-classification

distilbert/distilbert-base-uncased

finetune

apache-2.0

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TrainingArg

This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.9255
Accuracy: 0.6636

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: 5e-05
train_batch_size: 12
eval_batch_size: 12
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 12

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	74	1.2499	0.4864
No log	2.0	148	1.1182	0.6227
No log	3.0	222	1.2290	0.5409
No log	4.0	296	1.1244	0.6273
No log	5.0	370	1.2734	0.6545
No log	6.0	444	1.6389	0.6045
0.6739	7.0	518	1.5203	0.6636
0.6739	8.0	592	1.8517	0.6227
0.6739	9.0	666	1.8682	0.6591
0.6739	10.0	740	1.9589	0.6364
0.6739	11.0	814	1.9143	0.6545
0.6739	12.0	888	1.9255	0.6636

Framework versions

Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1

PiotrNaspinski/TrainingArg

TrainingArg

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

PiotrNaspinski/
TrainingArg