Downloads · 30 days
5
17% of all-time downloads
dimasik2987/1bdf01c7-e2c5-4cd5-9a6b-8847611f1f29
1bdf01c7-e2c5-4cd5-9a6b-8847611f1f29 is a machine learning model from dimasik2987. 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. --
Downloads · 30 days
5
17% of all-time downloads
All-time downloads
30
Public
Repo size
504 MB
Likes
0
Public
Click a slice to open those files.
.pt101 MB · 39%
From the Hugging Face model README
axolotl version: 0.4.1
adapter: lora
base_model: tiiuae/falcon-rw-1b
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- fb37409b08eaa6da_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/fb37409b08eaa6da_train_data.json
type:
field_input: tools
field_instruction: query
field_output: answers
format: '{instruction} {input}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
device: cuda
early_stopping_patience: 1
eval_max_new_tokens: 128
eval_steps: 5
eval_table_size: null
evals_per_epoch: null
flash_attention: false
fp16: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: false
hub_model_id: dimasik2987/1bdf01c7-e2c5-4cd5-9a6b-8847611f1f29
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: 3
lora_alpha: 32
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lr_scheduler: cosine
max_memory:
0: 79GiB
max_steps: 30
micro_batch_size: 2
mlflow_experiment_name: /tmp/fb37409b08eaa6da_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 1
optimizer: adamw_torch
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 10
sequence_len: 1024
special_tokens:
pad_token: <|endoftext|>
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: true
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 10e25596-312e-4395-a2b4-c145eb5dfbce
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 10e25596-312e-4395-a2b4-c145eb5dfbce
warmup_steps: 10
weight_decay: 0.01
xformers_attention: true
</details><br>
This model is a fine-tuned version of tiiuae/falcon-rw-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 | 1.6522 |
| 6.8585 | 0.0007 | 5 | 1.5762 |
| 5.8566 | 0.0014 | 10 | 1.2945 |
| 4.8929 | 0.0021 | 15 | 1.1622 |
| 4.6943 | 0.0028 | 20 | 1.0983 |
| 4.1838 | 0.0035 | 25 | 1.0764 |
| 4.1201 | 0.0042 | 30 | 1.0717 |