Aaron Renfroe
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---
license: apache-2.0
base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
tags:
- generated_from_trainer
model-index:
- name: OrcaMathTinyllama3
results: []
---
<!-- 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. -->
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<details><summary>See axolotl config</summary>
axolotl version: `0.4.0`
```yaml
base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
model_type: LlamaForCausalLM
tokenizer_type: LlamaTokenizer
load_in_8bit: false
load_in_4bit: false
strict: false
max_steps: 0
datasets:
- path: /home/renfroe/Dev/datasets/orcamath/orcamath-input-output.json
type:
system_prompt: ""
field_system: system
field_instruction: input
field_output: output
format: "<|user|>\n{instruction}</s>\n<|assistant|>\n"
no_input_format: "<|user|>\n{instruction}</s>\n<|assistant|>\n"
dataset_prepared_path:
val_set_size: 0.05
output_dir: ./OrcaMathTinyllama3
sequence_len: 2048
sample_packing: true
wandb_project: axolotl_tinyllama_orcamath
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 1
micro_batch_size: 10
num_epochs: 1
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0001
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
warmup_steps: 10
evals_per_epoch:
eval_table_size:
saves_per_epoch: 10
debug:
deepspeed:
weight_decay: 0.0001
fsdp:
fsdp_config:
special_tokens:
```
</details><br>
# OrcaMathTinyllama3
This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2366
## 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
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.2464 | 1.0 | 3773 | 0.2366 |
### Framework versions
- Transformers 4.40.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.18.0
- Tokenizers 0.15.0