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AlexHung29629 / fix_magistra4
Model's Last Updated: July 03 2025
text-generation
Introduction of fix_magistra4
Model Details of fix_magistra4
See axolotl config
axolotl version:
0.11.0.dev0
base_model: AlexHung29629/Magistral-Small-2506
tokenizer_use_mistral_common: false
plugins:
- axolotl.integrations.liger.LigerPlugin
liger_rope: true
liger_rms_norm: true
liger_glu_activation: true
liger_fused_linear_cross_entropy: true
unfrozen_parameters:
- ^lm_head.+$
- ^.+embed_tokens.+$
datasets:
- path: AlexHung29629/rr-mg-segmented
type: input_output
remove_unused_columns: false
sequence_len: 8192
sample_packing: true
eval_sample_packing: false
pad_to_sequence_len: true
use_tensorboard: true
save_only_model: true
gradient_accumulation_steps: 1
micro_batch_size: 1
num_epochs: 4
optimizer: adamw_torch_fused
#optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 1e-5
max_grad_norm: 1.0
adam_beta1: 0.9
adam_beta2: 0.95
adam_epsilon: 1e-8
bf16: true
tf32: false
warmup_ratio: 0.05
saves_per_epoch: 1
weight_decay: 0
train_on_inputs: false
flash_attention: true
#deepspeed: /workspace/output/zero3.json
fsdp:
- full_shard
- auto_wrap
fsdp_config:
fsdp_limit_all_gathers: true
fsdp_sync_module_states: true
fsdp_offload_params: false
fsdp_use_orig_params: true
fsdp_cpu_ram_efficient_loading: true
fsdp_activation_checkpointing: true
fsdp_transformer_layer_cls_to_wrap: MistralDecoderLayer
fsdp_state_dict_type: FULL_STATE_DICT
fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
seed: 42
hub_model_id: AlexHung29629/fix_magistra4
output_dir: /workspace/output/output_dir4
dataset_processes: 0
dataset_prepared_path: /workspace/output/dataset_prepared
torch_compile: false
added_tokens_overrides:
32: "[ARGS]"
33: "[CALL_ID]"
fix_magistra4
This model is a fine-tuned version of AlexHung29629/Magistral-Small-2506 on the AlexHung29629/rr-mg-segmented dataset.
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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 8
- total_eval_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.95) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 7
- training_steps: 140
Training results
Framework versions
- Transformers 4.52.4
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1
Runs of AlexHung29629 fix_magistra4 on huggingface.co
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More Information About fix_magistra4 huggingface.co Model
Url of fix_magistra4
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Provider of fix_magistra4 huggingface.co
Other API from AlexHung29629
Updated:October 31 2024
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