Arise-f
/

finetuning-sentiment-model-3000-samples

Text Classification

Generated from Trainer

text-embeddings-inference

Model card Files Files and versions

finetuning-sentiment-model-3000-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:

eval_loss: 0.6929
eval_model_preparation_time: 0.0016
eval_accuracy: 0.51
eval_f1: 0.0392
eval_runtime: 0.8962
eval_samples_per_second: 334.759
eval_steps_per_second: 21.201
epoch: 0
step: 0

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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 2

Framework versions

Transformers 5.16.1
Pytorch 2.14.0+cu130
Datasets 5.0.1
Tokenizers 0.23.2

Downloads last month: 3

Safetensors

Model size

67M params

Tensor type

F32

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Model tree for Arise-f/finetuning-sentiment-model-3000-samples

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distilbert/distilbert-base-uncased

Finetuned

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