metadata
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: togethercomputer/evo-1-8k-base
model-index:
- name: lora_evo_ta_all_layers_18_attention_layers
results: []
lora_evo_ta_all_layers_18_attention_layers
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: 2.8474
Model description
Trained on single ID token "5K dataset" filtered to 4k sequences (20% for test data)
lora_alpha = 64 <--------------
lora_dropout = 0.1
lora_r = 64 <---------
epochs = 3
learning rate = 3e-4
warmup_steps=500
gradient_accumulation_steps = 1
train_batch = 1
eval_batch = 1
ONLY ATTENTION LAYER <---------------------
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
- 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 |
---|---|---|---|
3.0886 | 0.375 | 1200 | 3.0465 |
3.0274 | 0.75 | 2400 | 2.9992 |
2.9835 | 1.125 | 3600 | 2.9622 |
2.9334 | 1.5 | 4800 | 2.9397 |
2.8989 | 1.875 | 6000 | 2.9026 |
2.8609 | 2.25 | 7200 | 2.8744 |
2.8413 | 2.625 | 8400 | 2.8584 |
2.8341 | 3.0 | 9600 | 2.8474 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1