---
license: apache-2.0
base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
tags:
- generated_from_trainer
model-index:
- name: tinyllama-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/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.3.0`
```yaml
base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
model_type: LlamaForCausalLM
tokenizer_type: LlamaTokenizer
is_llama_derived_model: true


eval_sample_packing: False #Poco dato

load_in_8bit: false
load_in_4bit: false
strict: false

datasets:
  - path: data.json # or json
    ds_type: json # see other options below
    type: completion

dataset_prepared_path:
val_set_size: 0.05
# output_dir: ./lora-out

sequence_len: 4096
sample_packing: true
pad_to_sequence_len: true

# adapter: lora
# lora_model_dir:
# lora_r: 32
# lora_alpha: 16
# lora_dropout: 0.05
# lora_target_linear: true
# lora_fan_in_fan_out:

wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
output_dir: ./tinyllama-out
gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 8 #2
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0002

train_on_inputs: false
group_by_length: false
bf16: true
fp16: false #TODO: change to true
tf32: false

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

save_strategy: "no"

warmup_steps: 10
evals_per_epoch: 4
# saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:

```

</details><br>

# tinyllama-out

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: 1.8806

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.9894        | 0.13  | 1    | 1.5790          |
| 1.915         | 0.26  | 2    | 1.4849          |
| 1.642         | 0.52  | 4    | 1.4032          |
| 1.5396        | 0.77  | 6    | 1.4059          |
| 1.3746        | 1.03  | 8    | 1.4101          |
| 0.9355        | 1.23  | 10   | 1.5147          |
| 0.9266        | 1.48  | 12   | 1.5291          |
| 0.8006        | 1.74  | 14   | 1.4724          |
| 0.7664        | 2.0   | 16   | 1.4965          |
| 0.4813        | 2.16  | 18   | 1.5715          |
| 0.4193        | 2.42  | 20   | 1.5436          |
| 0.364         | 2.68  | 22   | 1.6040          |
| 0.3592        | 2.94  | 24   | 1.5823          |
| 0.1884        | 3.13  | 26   | 1.6850          |
| 0.159         | 3.39  | 28   | 1.8316          |
| 0.1641        | 3.65  | 30   | 1.7286          |
| 0.1512        | 3.9   | 32   | 1.7029          |
| 0.1563        | 4.06  | 34   | 1.7033          |
| 0.0696        | 4.32  | 36   | 1.7482          |
| 0.0643        | 4.58  | 38   | 1.8069          |
| 0.0662        | 4.84  | 40   | 1.8410          |
| 0.0709        | 5.1   | 42   | 1.8529          |
| 0.0344        | 5.26  | 44   | 1.8626          |
| 0.0468        | 5.52  | 46   | 1.8716          |
| 0.0328        | 5.77  | 48   | 1.8761          |
| 0.0353        | 6.03  | 50   | 1.8789          |
| 0.0375        | 6.23  | 52   | 1.8803          |
| 0.0345        | 6.48  | 54   | 1.8802          |
| 0.0346        | 6.74  | 56   | 1.8806          |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.15.0