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intfloat-e5-small-v2-english-fp16-allagree – AI Model by abdulrahman-nuzha | AlphaNeural AI
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abdulrahman-nuzha
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intfloat-e5-small-v2-english-fp16-allagree
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transformers
tensorboard
safetensors
bert
text-classification
generated_from_trainer
intfloat/e5-small-v2
finetune
mit
autotrain_compatible
endpoints_compatible
us
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intfloat-e5-small-v2-english-fp16-allagree
This model is a fine-tuned version of
intfloat/e5-small-v2
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.5478
Accuracy: 0.7797
Precision: 0.8372
Recall: 0.7797
F1: 0.7220
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
1.0007
3.3448
50
0.8869
0.5859
0.7574
0.5859
0.4329
0.6263
6.6897
100
0.5478
0.7797
0.8372
0.7797
0.7220
Framework versions
Transformers 4.48.2
Pytorch 2.6.0+cu124
Datasets 3.3.1
Tokenizers 0.21.0
