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Alphatao/0a07cf8f-77d2-43ad-a6e9-89f401e8ec49
0a07cf8f-77d2-43ad-a6e9-89f401e8ec49 is a machine learning model from Alphatao. 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 mit.
should probably proofread and complete it, then remove this comment. --
Downloads · 30 days
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.json4.6 MB · 90%
From the Hugging Face model README
axolotl version: 0.4.1
adapter: lora
base_model: fxmarty/really-tiny-falcon-testing
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- e8ef6edb66e20da7_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/e8ef6edb66e20da7_train_data.json
type:
field_input: input
field_instruction: instruction
field_output: output
format: '{instruction} {input}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
device_map:
? ''
: 0,1,2,3,4,5,6,7
early_stopping_patience: 2
eval_max_new_tokens: 128
eval_steps: 100
eval_table_size: null
flash_attention: false
gradient_accumulation_steps: 8
gradient_checkpointing: true
group_by_length: false
hub_model_id: Alphatao/0a07cf8f-77d2-43ad-a6e9-89f401e8ec49
hub_repo: null
hub_strategy: null
hub_token: null
learning_rate: 0.0002
load_best_model_at_end: true
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 128
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lora_target_modules:
- q_proj
- k_proj
- v_proj
- o_proj
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 2520
micro_batch_size: 4
mlflow_experiment_name: /tmp/e8ef6edb66e20da7_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 2
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 100
sequence_len: 2048
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 6f911363-8c0f-4331-9742-a2fb57ee53b7
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 6f911363-8c0f-4331-9742-a2fb57ee53b7
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null
</details><br>
This model is a fine-tuned version of fxmarty/really-tiny-falcon-testing on the None dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 88.7573 | 0.0005 | 1 | 11.0922 |
| 86.6896 | 0.0503 | 100 | 10.8462 |
| 86.5276 | 0.1007 | 200 | 10.8125 |
| 86.4563 | 0.1510 | 300 | 10.7933 |
| 86.4675 | 0.2013 | 400 | 10.7781 |
| 86.3597 | 0.2517 | 500 | 10.7711 |
| 86.2831 | 0.3020 | 600 | 10.7652 |
| 86.2862 | 0.3523 | 700 | 10.7596 |
| 86.0115 | 0.4027 | 800 | 10.7555 |
| 86.0142 | 0.4530 | 900 | 10.7527 |
| 86.0606 | 0.5033 | 1000 | 10.7495 |
| 86.0031 | 0.5537 | 1100 | 10.7475 |
| 86.0867 | 0.6040 | 1200 | 10.7452 |
| 86.0885 | 0.6543 | 1300 | 10.7447 |
| 85.8223 | 0.7047 | 1400 | 10.7435 |
| 85.5493 | 0.7550 | 1500 | 10.7415 |
| 86.2632 | 0.8053 | 1600 | 10.7404 |
| 86.1295 | 0.8557 | 1700 | 10.7397 |
| 86.1934 | 0.9060 | 1800 | 10.7389 |
| 85.7078 | 0.9563 | 1900 | 10.7383 |
| 85.986 | 1.0067 | 2000 | 10.7382 |
| 86.2705 | 1.0570 | 2100 | 10.7379 |
| 86.2735 | 1.1073 | 2200 | 10.7377 |
| 86.3739 | 1.1577 | 2300 | 10.7376 |
| 86.1081 | 1.2080 | 2400 | 10.7376 |
| 85.8134 | 1.2583 | 2500 | 10.7376 |