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results_packing – AI Model by andrewAmani | AlphaNeural AI
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results_packing
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safetensors
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hivaze/ParaLex-Llama-3-8B-SFT
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results_packing
This model is a fine-tuned version of
hivaze/ParaLex-Llama-3-8B-SFT
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.8083
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: 1
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 17
total_train_batch_size: 17
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
num_epochs: 8
Training results
Training Loss
Epoch
Step
Validation Loss
7.3306
1.25
5
5.9428
5.4669
2.5
10
4.3334
4.0282
3.75
15
3.1156
2.9271
5.0
20
2.3114
2.3074
6.25
25
1.9202
1.9795
7.5
30
1.8083
Framework versions
PEFT 0.11.1
Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1
