See axolotl config
axolotl version: 0.4.1
base_model: Fischerboot/LLama3-Lexi-Aura-3Some-SLERP-SLERP-ql-merge
model_type: LlamaForCausalLM
tokenizer_type: AutoTokenizer
load_in_8bit: false
load_in_4bit: true
strict: false
chat_template: llama3
datasets:
- path: Fischerboot/newnewdataset-sophie
type: sharegpt
- path: PJMixers/grimulkan_theory-of-mind-ShareGPT
type: sharegpt
conversation: llama3
dataset_prepared_path: last_run_prepared
val_set_size: 0.1
output_dir: ./outputs/256-rank-2-datasets
adapter: qlora
lora_model_dir:
sequence_len: 128
sample_packing: false
pad_to_sequence_len: true
lora_r: 256
lora_alpha: 128
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
- gate_proj
- down_proj
- up_proj
- q_proj
- v_proj
- k_proj
- o_proj
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 1
micro_batch_size: 1
num_epochs: 8
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
loss_watchdog_threshold: 5.0
loss_watchdog_patience: 3
eval_sample_packing: false
warmup_steps: 10
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
bos_token: "<|begin_of_text|>"
eos_token: "<|end_of_text|>"
pad_token: "<|end_of_text|>"
outputs/256-rank-2-datasets
This model is a fine-tuned version of Fischerboot/LLama3-Lexi-Aura-3Some-SLERP-SLERP-ql-merge on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4406
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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 6.1066 | 0.0034 | 1 | 6.0671 |
| 0.2818 | 0.2526 | 74 | 0.6377 |
| 0.5131 | 0.5051 | 148 | 0.4845 |
| 0.4376 | 0.7577 | 222 | 0.4022 |
| 0.3492 | 1.0102 | 296 | 0.3534 |
| 0.3393 | 1.2628 | 370 | 0.3735 |
| 0.4548 | 1.5154 | 444 | 0.4114 |
| 0.5944 | 1.7679 | 518 | 0.4224 |
| 0.3372 | 2.0205 | 592 | 0.3720 |
| 0.5017 | 2.2730 | 666 | 0.4280 |
| 0.2303 | 2.5256 | 740 | 0.3827 |
| 0.2586 | 2.7782 | 814 | 0.3366 |
| 0.1802 | 3.0307 | 888 | 0.3832 |
| 0.3442 | 3.2833 | 962 | 0.3267 |
| 0.1136 | 3.5358 | 1036 | 0.3215 |
| 0.144 | 3.7884 | 1110 | 0.3031 |
| 0.2701 | 4.0410 | 1184 | 0.2889 |
| 0.1677 | 4.2935 | 1258 | 0.3019 |
| 0.2538 | 4.5461 | 1332 | 0.3172 |
| 0.1108 | 4.7986 | 1406 | 0.2773 |
| 0.1633 | 5.0512 | 1480 | 0.2980 |
| 0.1342 | 5.3038 | 1554 | 0.2953 |
| 0.1557 | 5.5563 | 1628 | 0.3226 |
| 0.2 | 5.8089 | 1702 | 0.3255 |
| 0.0051 | 6.0614 | 1776 | 0.3302 |
| 0.0164 | 6.3140 | 1850 | 0.3817 |
| 0.0249 | 6.5666 | 1924 | 0.4169 |
| 0.1055 | 6.8191 | 1998 | 0.4275 |
| 0.0044 | 7.0717 | 2072 | 0.4351 |
| 0.0156 | 7.3242 | 2146 | 0.4392 |
| 0.0524 | 7.5768 | 2220 | 0.4393 |
| 0.0382 | 7.8294 | 2294 | 0.4406 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.1.2+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1
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