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phi2_mrqa_v2 – AI Model by enriquesaou | AlphaNeural AI
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enriquesaou
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phi2_mrqa_v2
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peft
tensorboard
safetensors
generated_from_trainer
microsoft/phi-2
adapter
mit
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phi2_mrqa_v2
This model is a fine-tuned version of
microsoft/phi-2
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.1123
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: 4
total_train_batch_size: 4
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.03
training_steps: 800
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
1.5938
0.5
100
1.2202
1.2563
1.0
200
1.1830
1.2218
1.5
300
1.1568
1.1537
2.0
400
1.1370
1.1376
2.5
500
1.1254
1.2026
3.0
600
1.1177
1.1269
3.5
700
1.1137
1.1692
4.0
800
1.1123
Framework versions
PEFT 0.10.1.dev0
Transformers 4.41.0.dev0
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1
