CoolFace
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eeeebbb2/bd2df650-ef52-4589-a762-313905b5420e

sourceHugging Facemitupdated 2y agoView on Hugging Face
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Model Card

<!-- 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: 0.4.1

yaml
adapter: lora
base_model: fxmarty/really-tiny-falcon-testing
bf16: auto
chat_template: llama3
cosine_min_lr_ratio: 0.1
data_processes: 4
dataset_prepared_path: null
datasets:
- data_files:
  - 99c3033a220f8ac7_train_data.json
  ds_type: json
  format: custom
  num_proc: 4
  path: /workspace/input_data/99c3033a220f8ac7_train_data.json
  streaming: true
  type:
    field_input: input_translation
    field_instruction: input
    field_output: id
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
device_map: balanced
do_eval: true
early_stopping_patience: 1
eval_batch_size: 1
eval_sample_packing: false
eval_steps: 25
evaluation_strategy: steps
flash_attention: false
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 16
gradient_checkpointing: true
group_by_length: true
hub_model_id: eeeebbb2/bd2df650-ef52-4589-a762-313905b5420e
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0001
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 64
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 32
lora_target_linear: true
lora_target_modules:
- q_proj
- v_proj
lr_scheduler: cosine
max_grad_norm: 1.0
max_memory:
  0: 75GB
  1: 75GB
  2: 75GB
  3: 75GB
max_steps: 50
micro_batch_size: 2
mixed_precision: bf16
mlflow_experiment_name: /tmp/99c3033a220f8ac7_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optim_args:
  adam_beta1: 0.9
  adam_beta2: 0.95
  adam_epsilon: 1e-5
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: 25
save_strategy: steps
sequence_len: 2048
strict: false
tf32: false
tokenizer_type: AutoTokenizer
torch_compile: false
train_on_inputs: false
trust_remote_code: true
val_set_size: 50
wandb_entity: null
wandb_mode: online
wandb_name: bd2df650-ef52-4589-a762-313905b5420e
wandb_project: Public_TuningSN
wandb_runid: bd2df650-ef52-4589-a762-313905b5420e
warmup_ratio: 0.04
weight_decay: 0.01
xformers_attention: null

</details><br>

bd2df650-ef52-4589-a762-313905b5420e

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:

  • —Loss: 10.9100

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: 0.0001
  • —trainbatchsize: 2
  • —evalbatchsize: 1
  • —seed: 42
  • —distributed_type: multi-GPU
  • —num_devices: 4
  • —gradientaccumulationsteps: 16
  • —totaltrainbatch_size: 128
  • —totalevalbatch_size: 4
  • —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=adambeta1=0.9,adambeta2=0.95,adam_epsilon=1e-5
  • —lrschedulertype: cosine
  • —lrschedulerwarmup_steps: 2
  • —training_steps: 50

Training results

Training LossEpochStepValidation Loss
177.26250.0244111.0615
175.18750.60982510.9495
174.3251.21955010.9100

Framework versions

  • —PEFT 0.13.2
  • —Transformers 4.46.0
  • —Pytorch 2.5.0+cu124
  • —Datasets 3.0.1
  • —Tokenizers 0.20.1