---
license: mit
base_model: microsoft/phi-2
tags:
- axolotl
- generated_from_trainer
model-index:
- name: phi2-filter2
  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: microsoft/phi-2
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
trust_remote_code: true

load_in_8bit: false
load_in_4bit: false
strict: false

hub_model_id: satpalsr/phi2-filter2
hf_use_auth_token: true

datasets:
  - path: satpalsr/translation-filter
    type: completion

dataset_prepared_path:
val_set_size: 0.01
output_dir: ./phi-sft-out2

sequence_len: 2048
sample_packing: false  # currently unsupported
pad_to_sequence_len:

adapter:
lora_model_dir:
lora_r: 16
lora_alpha: 32
lora_dropout: 0.1
lora_target_linear: true
lora_fan_in_fan_out:
lora_modules_to_save:
  - embd
  - lm_head

wandb_project: phi2transfilter
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:

gradient_accumulation_steps: 1
micro_batch_size: 16
num_epochs: 4
optimizer: paged_adamw_8bit
adam_beta2: 0.95
adam_epsilon: 0.00001
max_grad_norm: 1.0
lr_scheduler: cosine
learning_rate: 1e-5

train_on_inputs: false
group_by_length: false
bf16: true
fp16: false
tf32: true

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

warmup_steps: 100
evals_per_epoch: 4
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.1
fsdp:
fsdp_config:
resize_token_embeddings_to_32x: true
special_tokens:
  pad_token: "<|endoftext|>"
```

</details><br>

# phi2-filter2

This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1944

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.5676        | 0.01  | 1    | 2.5391          |
| 2.4364        | 0.25  | 29   | 2.4042          |
| 1.9523        | 0.5   | 58   | 1.8580          |
| 1.1137        | 0.75  | 87   | 0.9535          |
| 0.5107        | 1.0   | 116  | 0.4195          |
| 0.4588        | 1.25  | 145  | 0.2877          |
| 0.2876        | 1.5   | 174  | 0.2462          |
| 0.2959        | 1.75  | 203  | 0.2264          |
| 0.2197        | 2.0   | 232  | 0.2114          |
| 0.3045        | 2.25  | 261  | 0.2052          |
| 0.2726        | 2.5   | 290  | 0.2022          |
| 0.3046        | 2.75  | 319  | 0.1975          |
| 0.3316        | 3.0   | 348  | 0.1954          |
| 0.2223        | 3.25  | 377  | 0.1950          |
| 0.2609        | 3.5   | 406  | 0.1946          |
| 0.2739        | 3.75  | 435  | 0.1945          |
| 0.2703        | 4.0   | 464  | 0.1944          |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.1+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0