Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
finetuned_model_on-4k-samples – AI Model by Wolverine001 | AlphaNeural AI
You can deploy this model and start earning money today!
Wolverine001
/
finetuned_model_on-4k-samples
like
0
transformers
safetensors
distilbert
text-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
finetuned_model_on-4k-samples
This model is a fine-tuned version of
distilbert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.5070
Accuracy: 0.8379
F1 Macro: 0.8347
F1 Weighted: 0.8380
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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1 Macro
F1 Weighted
0.5616
1.0
350
0.5412
0.795
0.7912
0.7947
0.3281
2.0
700
0.5039
0.825
0.8201
0.8246
0.1472
3.0
1050
0.5070
0.8379
0.8347
0.8380
Framework versions
Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1
