metadata

library_name: transformers
license: mit
base_model: intfloat/e5-small
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: intfloat-e5-small-english-fp16-allagree
    results: []

intfloat-e5-small-english-fp16-allagree

This model is a fine-tuned version of intfloat/e5-small on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.5311
Accuracy: 0.9251
Precision: 0.9257
Recall: 0.9251
F1: 0.9233

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: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 128
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
lr_scheduler_warmup_ratio: 0.3
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
1.0153	3.3448	50	0.9323	0.5859	0.7574	0.5859	0.4329
0.6758	6.6897	100	0.5311	0.9251	0.9257	0.9251	0.9233

Framework versions

Transformers 4.48.2
Pytorch 2.6.0+cu124
Datasets 3.3.1
Tokenizers 0.21.0