Holland-4B-V1 / README.md
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---
library_name: transformers
license: other
base_model: IntervitensInc/Llama-3.1-Minitron-4B-Width-Base-chatml
tags:
- generated_from_trainer
model-index:
- name: outputs/out
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. -->
[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<details><summary>See axolotl config</summary>
axolotl version: `0.4.1`
```yaml
base_model: IntervitensInc/Llama-3.1-Minitron-4B-Width-Base-chatml
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
load_in_8bit: false
load_in_4bit: false
strict: false
datasets:
- path: NewEden/Gryphe-3.5-16k-Subset
type: sharegpt
conversation: chatml
- path: Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
type: sharegpt
conversation: chatml
- path: anthracite-org/kalo-opus-instruct-22k-no-refusal
type: sharegpt
conversation: chatml
- path: PJMixers/lodrick-the-lafted_OpusStories-ShareGPT
type: sharegpt
conversation: chatml
chat_template: chatml
val_set_size: 0.01
output_dir: ./outputs/out
adapter:
lora_r:
lora_alpha:
lora_dropout:
lora_target_linear:
sequence_len: 16384
# sequence_len: 32768
sample_packing: true
eval_sample_packing: false
pad_to_sequence_len: true
plugins:
- axolotl.integrations.liger.LigerPlugin
liger_rope: true
liger_rms_norm: true
liger_swiglu: true
liger_fused_linear_cross_entropy: true
wandb_project: Ohashi4b
wandb_entity:
wandb_watch:
wandb_name: Ohashi4b
wandb_log_model:
gradient_accumulation_steps: 32
micro_batch_size: 1
num_epochs: 2
optimizer: adamw_bnb_8bit
#optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 0.00002
weight_decay: 0.05
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: true
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
warmup_ratio: 0.1
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 1
debug:
deepspeed: /workspace/axolotl/deepspeed_configs/zero2.json
#deepspeed:
fsdp:
fsdp_config:
special_tokens:
pad_token: <|finetune_right_pad_id|>
```
</details><br>
# outputs/out
This model is a fine-tuned version of [IntervitensInc/Llama-3.1-Minitron-4B-Width-Base-chatml](https://huggingface.co./IntervitensInc/Llama-3.1-Minitron-4B-Width-Base-chatml) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0118
## 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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 32
- total_train_batch_size: 64
- total_eval_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 6
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.4992 | 0.0278 | 1 | 1.6105 |
| 1.2866 | 0.25 | 9 | 1.2680 |
| 1.1737 | 0.5 | 18 | 1.1396 |
| 1.1355 | 0.75 | 27 | 1.0766 |
| 1.1065 | 1.0 | 36 | 1.0408 |
| 0.9673 | 1.2370 | 45 | 1.0272 |
| 0.9526 | 1.4870 | 54 | 1.0167 |
| 0.9653 | 1.7370 | 63 | 1.0126 |
| 0.958 | 1.9870 | 72 | 1.0118 |
### Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1