Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
finetuning-sentiment-model-5000-samples – AI Model by hseguraq | AlphaNeural AI
You can deploy this model and start earning money today!
hseguraq
/
finetuning-sentiment-model-5000-samples
like
0
transformers
tensorboard
safetensors
distilbert
text-classification
generated_from_trainer
distilbert/distilbert-base-uncased-finetuned-sst-2-english
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
finetuning-sentiment-model-5000-samples
This model is a fine-tuned version of
distilbert-base-uncased-finetuned-sst-2-english
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.3309
Accuracy: 0.9156
F1: 0.9436
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: 1e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
No log
1.0
254
0.2906
0.8844
0.9263
0.2482
2.0
508
0.2648
0.9067
0.9371
0.2482
3.0
762
0.3114
0.92
0.9472
0.1236
4.0
1016
0.3309
0.9156
0.9436
Framework versions
Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1
