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abaddon182/e432b9e4-2d75-4003-91bd-613d13729b92
e432b9e4-2d75-4003-91bd-613d13729b92 is a machine learning model from abaddon182. 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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From the Hugging Face model README
axolotl version: 0.4.1
adapter: lora
base_model: EleutherAI/pythia-1b
bf16: auto
chat_template: llama3
dataloader_num_workers: 12
dataset_prepared_path: null
datasets:
- data_files:
- 6a701a4bc394f427_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/6a701a4bc394f427_train_data.json
type:
field_instruction: text_description
field_output: text
format: '{instruction}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
device_map: auto
do_eval: true
early_stopping_patience: 3
eval_batch_size: 8
eval_max_new_tokens: 128
eval_steps: 150
eval_table_size: null
evals_per_epoch: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 2
gradient_checkpointing: true
group_by_length: true
hub_model_id: abaddon182/e432b9e4-2d75-4003-91bd-613d13729b92
hub_repo: null
hub_strategy: end
hub_token: null
learning_rate: 3e-5
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 10
lora_alpha: 128
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_memory:
0: 75GB
max_steps: 1500
micro_batch_size: 8
mlflow_experiment_name: /tmp/6a701a4bc394f427_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 15
optim_args:
adam_beta1: 0.9
adam_beta2: 0.999
adam_epsilon: 1e-8
optimizer: adamw_torch
output_dir: miner_id_24
pad_to_sequence_len: false
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 150
saves_per_epoch: null
sequence_len: 1024
special_tokens:
pad_token: <|endoftext|>
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: dd333359-fa9b-48db-bf56-6c6be8149792
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: dd333359-fa9b-48db-bf56-6c6be8149792
warmup_steps: 50
weight_decay: 0.1
xformers_attention: null
</details><br>
This model is a fine-tuned version of EleutherAI/pythia-1b 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 |
|---|---|---|---|
| No log | 0.0001 | 1 | 4.8305 |
| 7.0881 | 0.0165 | 150 | 3.4144 |
| 6.669 | 0.0329 | 300 | 3.3707 |
| 6.8888 | 0.0494 | 450 | 3.3564 |
| 6.5959 | 0.0658 | 600 | 3.3436 |
| 6.7722 | 0.0823 | 750 | 3.3378 |
| 6.9875 | 0.0987 | 900 | 3.3323 |
| 6.6995 | 0.1152 | 1050 | 3.3278 |
| 6.6823 | 0.1317 | 1200 | 3.3284 |
| 6.7327 | 0.1481 | 1350 | 3.3265 |
| 6.8971 | 0.1646 | 1500 | 3.3267 |