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lora_evo_ta_all_layers_16 – AI Model by lsmille | AlphaNeural AI
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lsmille
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lora_evo_ta_all_layers_16
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peft
safetensors
generated_from_trainer
togethercomputer/evo-1-8k-base
adapter
apache-2.0
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lora_evo_ta_all_layers_16
This model is a fine-tuned version of
togethercomputer/evo-1-8k-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 2.5463
Model description
Trained on single ID token 5K dataset filtered to 10k sequences (20% for test data = 2000)
lora_alpha = 128
lora_dropout = 0.1
lora_r = 128
epochs = 3
learning rate = 3e-4
warmup_steps=200
gradient_accumulation_steps = 1
train_batch = 2
eval_batch = 2
ONLY on attention layers and MLPs of last 31 layers <--------------------
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: 0.0003
train_batch_size: 2
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant
lr_scheduler_warmup_steps: 500
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
2.8598
0.4998
1999
2.6289
2.5927
0.9995
3998
2.5852
2.5467
1.4992
5997
2.5717
2.5487
1.999
7996
2.5554
2.4987
2.4988
9995
2.5546
2.4934
2.9985
11994
2.5463
Framework versions
PEFT 0.11.1
Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1
