lora_evo_ta_all_layers_2

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lora_evo_ta_all_layers_2

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: 3.1660

Model description

lora_alpha = 32

lora_dropout = 0.05

lora_r = 16

epochs = 9 <---------------

learning rate = 3e-4

warmup_steps=0.5

gradient_accumulation_steps = 8

train_batch = 1

eval_batch = 1

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: 1
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: constant
• lr_scheduler_warmup_steps: 0.5
• num_epochs: 9

Training results

Framework versions

• PEFT 0.11.1
• Transformers 4.41.1
• Pytorch 2.3.0+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1