illuin-explo/CroissantLLM_ft_translation_correction
022
<!-- 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"/> <details><summary>See axolotl config</summary>
axolotl version: 0.4.0
base_model: croissantllm/CroissantCool-v0.2
model_type: LlamaForCausalLM
tokenizer_type: LlamaTokenizerFast
is_llama_derived_model: true
special_tokens:
bos_token: "<s>"
eos_token: "</s>"
unk_token: "<unk>"
tokens:
- "<|im_start|>"
- "<|im_end|>"
load_in_8bit: false
load_in_4bit: false
strict: false
datasets:
- path: manu/dataset_1
split: train
type: sharegpt
chat_template: "chatml"
default_system_message: null
dataset_prepared_path: new_pii_2
val_set_size: 0.05
output_dir: /gpfs/workdir/fayssema/models/out_newtok_dataset1
sequence_len: 2048
sample_packing: false
pad_to_sequence_len: false
adapter:
lora_model_dir:
lora_r:
lora_alpha:
lora_dropout:
lora_target_linear:
lora_fan_in_fan_out:
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 2
micro_batch_size: 16
num_epochs: 3
# optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.00003
train_on_inputs: false
group_by_length: false
bf16: auto
fp16: false
tf32: true
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
flash_attn_cross_entropy: false
flash_attn_rms_norm: true
flash_attn_fuse_qkv: false
flash_attn_fuse_mlp: true
warmup_steps: 100
evals_per_epoch: 4
eval_table_size:
saves_per_epoch: 1
debug:
deepspeed: #deepspeed_configs/zero2.json # multi-gpu only
weight_decay: 0.05
fsdp:
fsdp_config:
</details><br>
gpfs/workdir/fayssema/models/outnewtokdataset1
This model is a fine-tuned version of croissantllm/CroissantCool-v0.2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0087
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: 3e-05
- trainbatchsize: 16
- evalbatchsize: 16
- seed: 42
- gradientaccumulationsteps: 2
- totaltrainbatch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lrschedulertype: cosine
- lrschedulerwarmup_steps: 100
- num_epochs: 3
Training results
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0