See axolotl config
axolotl version: 0.4.1
base_model: fxmarty/tiny-random-GemmaForCausalLM
batch_size: 32
bf16: true
chat_template: tokenizer_default_fallback_alpaca
datasets:
- data_files:
- b7c2a4a781c93416_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/b7c2a4a781c93416_train_data.json
type:
field_input: context
field_instruction: question
field_output: answer
format: '{instruction} {input}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
eval_steps: 20
flash_attention: true
gpu_memory_limit: 80GiB
gradient_checkpointing: true
group_by_length: true
hub_model_id: willtensora/fd1980a0-7e71-4e52-addb-318dca5991d5
hub_strategy: checkpoint
learning_rate: 0.0002
logging_steps: 10
lr_scheduler: cosine
max_steps: 2500
micro_batch_size: 4
model_type: AutoModelForCausalLM
optimizer: adamw_bnb_8bit
output_dir: /workspace/axolotl/configs
pad_to_sequence_len: true
resize_token_embeddings_to_32x: false
sample_packing: false
save_steps: 40
save_total_limit: 1
sequence_len: 2048
tokenizer_type: GemmaTokenizerFast
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.1
wandb_entity: ''
wandb_mode: online
wandb_name: fxmarty/tiny-random-GemmaForCausalLM-/workspace/input_data/b7c2a4a781c93416_train_data.json
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: default
warmup_ratio: 0.05
xformers_attention: true
fd1980a0-7e71-4e52-addb-318dca5991d5
This model is a fine-tuned version of fxmarty/tiny-random-GemmaForCausalLM on the None dataset. It achieves the following results on the evaluation set:
- Loss: 11.7971
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
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 7
- training_steps: 156
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 0.0008 | 1 | 12.4537 |
12.4357 | 0.0161 | 20 | 12.4267 |
12.392 | 0.0322 | 40 | 12.3762 |
12.3026 | 0.0483 | 60 | 12.2651 |
12.1177 | 0.0645 | 80 | 12.0658 |
11.9286 | 0.0806 | 100 | 11.8860 |
11.8324 | 0.0967 | 120 | 11.8100 |
11.798 | 0.1128 | 140 | 11.7971 |
Framework versions
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
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Inference Providers
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the model is not deployed on the HF Inference API.
Model tree for willtensora/fd1980a0-7e71-4e52-addb-318dca5991d5
Base model
fxmarty/tiny-random-GemmaForCausalLM