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lora-color-tiny
nassersala/lora-color-tiny
lora-color-tiny is a machine learning model from nassersala. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- apache-2.0
- Model type
- llama
- Access
- Public
- Created
- May 27, 2024
- Updated
- May 27, 2024
- SHA
- 9e1f2134
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
<details><summary>See axolotl config</summary>
axolotl version: 0.4.0
base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
model_type: LlamaForCausalLM
tokenizer_type: LlamaTokenizer
load_in_8bit: true
load_in_4bit: false
strict: false
datasets:
- path: burkelibbey/colors
type:
field_instruction: color
field_output: description
conversation: chatml
chat_template: chatml
dataset_prepared_path:
val_set_size: 0.05
output_dir: ./outputs/lora-out
sequence_len: 4096
sample_packing: true
eval_sample_packing: false
pad_to_sequence_len: true
adapter: lora
lora_model_dir:
lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 4
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0002
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
warmup_steps: 10
evals_per_epoch: 4
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
outputs/lora-out
This model is a fine-tuned version of TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2375
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: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.7509 | 0.0204 | 1 | 2.6902 |
| 1.8064 | 0.2653 | 13 | 1.6735 |
| 1.5513 | 0.5306 | 26 | 1.4832 |
| 1.482 | 0.7959 | 39 | 1.4111 |
| 1.392 | 1.0408 | 52 | 1.3677 |
| 1.3414 | 1.3061 | 65 | 1.3319 |
| 1.3213 | 1.5714 | 78 | 1.3029 |
| 1.3028 | 1.8367 | 91 | 1.2795 |
| 1.2761 | 2.0816 | 104 | 1.2697 |
| 1.2509 | 2.3469 | 117 | 1.2587 |
| 1.2884 | 2.6122 | 130 | 1.2472 |
| 1.254 | 2.8776 | 143 | 1.2410 |
| 1.2523 | 3.1224 | 156 | 1.2403 |
| 1.2468 | 3.3878 | 169 | 1.2385 |
| 1.2476 | 3.6531 | 182 | 1.2370 |
| 1.2366 | 3.9184 | 195 | 1.2375 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.1.2+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1
- Library
- peft
- Type
- llama
- License
- apache-2.0
- Created
- May 27, 2024
- Updated
- May 27, 2024