metadata
library_name: peft
base_model: microsoft/codebert-base
tags:
- generated_from_trainer
model-index:
- name: codebert-emotion-model
results: []
codebert-emotion-model
This model is a fine-tuned version of microsoft/codebert-base on an unknown dataset. It achieves the following results on the evaluation set:
- eval_loss: 1.9961
- eval_model_preparation_time: 0.0041
- eval_accuracy: 0.095
- eval_f1: 0.0165
- eval_precision: 0.0090
- eval_recall: 0.095
- eval_runtime: 17.4943
- eval_samples_per_second: 11.432
- eval_steps_per_second: 2.858
- 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Framework versions
- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1