Aivesa/f4b59c1d-77a9-43a6-91d0-300d566b42ae
014
<!-- 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. -->
<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/> <details><summary>See axolotl config</summary>
axolotl version: 0.6.0
adapter: lora
base_model: unsloth/tinyllama
bf16: auto
chat_template: llama3
dataset_prepared_path: /workspace/axolotl/data/prepared
datasets:
- ds_type: json
format: custom
path: Aivesa/dataset_b30e43a3-126d-4120-a4a8-cefb93430cce
type:
field_instruction: instruction
field_output: output
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 128
eval_table_size: null
evals_per_epoch: 4
flash_attention: false
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: false
group_by_length: false
hub_model_id: Aivesa/f4b59c1d-77a9-43a6-91d0-300d566b42ae
hub_private_repo: true
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 16
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 8
lora_target_linear: true
lr_scheduler: cosine
max_steps: 10
micro_batch_size: 2
model_type: AutoModelForCausalLM
num_epochs: 1
optimizer: adamw_bnb_8bit
output_dir: /workspace/axolotl/outputs
pad_to_sequence_len: true
push_to_hub: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_safetensors: true
saves_per_epoch: 4
sequence_len: 512
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
use_accelerate: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: b30e43a3-126d-4120-a4a8-cefb93430cce
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: b30e43a3-126d-4120-a4a8-cefb93430cce
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null
</details><br>
f4b59c1d-77a9-43a6-91d0-300d566b42ae
This model is a fine-tuned version of unsloth/tinyllama on the Aivesa/dataset_b30e43a3-126d-4120-a4a8-cefb93430cce dataset. It achieves the following results on the evaluation set:
- Loss: 2.1677
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
- trainbatchsize: 2
- evalbatchsize: 2
- seed: 42
- gradientaccumulationsteps: 4
- totaltrainbatch_size: 8
- optimizer: Use adamwbnb8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lrschedulertype: cosine
- lrschedulerwarmup_steps: 10
- training_steps: 10
Training results
Framework versions
- PEFT 0.14.0
- Transformers 4.47.1
- Pytorch 2.5.0a0+e000cf0ad9.nv24.10
- Datasets 3.1.0
- Tokenizers 0.21.0