0b30b36285
Model: magnifi/magnifi-module-classifier-04-17-relabelled-upsampled Source: Original Platform
152 lines
4.5 KiB
Markdown
152 lines
4.5 KiB
Markdown
---
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library_name: transformers
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license: apache-2.0
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base_model: Tifin-Sage/magnifi-classifier-01-05-search-agent-3-epochs-3k-unknown-errors
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tags:
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- axolotl
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- generated_from_trainer
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datasets:
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- Tifin-Sage/magnifi-module-classifier-04-17-relabelled-upsampled
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model-index:
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- name: magnifi-module-classifier-04-17-relabelled-upsampled
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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[<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)
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<details><summary>See axolotl config</summary>
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axolotl version: `0.16.0.dev0`
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```yaml
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base_model: Tifin-Sage/magnifi-classifier-01-05-search-agent-3-epochs-3k-unknown-errors
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hub_model_id: Tifin-Sage/magnifi-module-classifier-04-17-relabelled-upsampled
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load_in_8bit: false
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load_in_4bit: false
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strict: false
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chat_template: qwen3
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datasets:
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- path: Tifin-Sage/magnifi-module-classifier-04-17-relabelled-upsampled
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type: chat_template
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split: train
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field_messages: messages
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message_property_mappings:
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role: role
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content: content
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val_set_size: 0.1
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output_dir: /workspace/data/outputs/qwen3-4B/fft_magnifi-module-classifier-04-17-relabelled-upsampled/
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dataset_prepared_path: /workspace/data/datasets_prepared/magnifi-module-classifier-04-17-relabelled-upsampled
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sequence_len: 16000
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sample_packing: true
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eval_sample_packing: true
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wandb_project: sage-classifier
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wandb_entity:
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wandb_watch:
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wandb_name: magnifi-module-classifier-04-17-relabelled-upsampled
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wandb_log_model:
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gradient_accumulation_steps: 1
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micro_batch_size: 1
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num_epochs: 2
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optimizer: adamw_torch_fused
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lr_scheduler: cosine
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learning_rate: 2e-5
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bf16: auto
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tf32: true
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resume_from_checkpoint:
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logging_steps: 1
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evals_per_epoch: 2
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saves_per_epoch: 1
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warmup_ratio: 0.1
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weight_decay: 0.0
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fsdp:
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- full_shard
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- auto_wrap
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fsdp_config:
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fsdp_version: 2
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fsdp_offload_params: false
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fsdp_cpu_ram_efficient_loading: true
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fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
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fsdp_transformer_layer_cls_to_wrap: Qwen3DecoderLayer
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fsdp_state_dict_type: FULL_STATE_DICT
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fsdp_sharding_strategy: FULL_SHARD
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fsdp_reshard_after_forward: true
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fsdp_activation_checkpointing: true
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special_tokens:
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```
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</details><br>
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# magnifi-module-classifier-04-17-relabelled-upsampled
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This model is a fine-tuned version of [Tifin-Sage/magnifi-classifier-01-05-search-agent-3-epochs-3k-unknown-errors](https://huggingface.co/Tifin-Sage/magnifi-classifier-01-05-search-agent-3-epochs-3k-unknown-errors) on the Tifin-Sage/magnifi-module-classifier-04-17-relabelled-upsampled dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2227
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- Ppl: 1.2494
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- Memory/max Active (gib): 34.91
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- Memory/max Allocated (gib): 34.91
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- Memory/device Reserved (gib): 57.25
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 2
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- total_train_batch_size: 2
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- total_eval_batch_size: 2
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 47
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- training_steps: 478
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Ppl | Active (gib) | Allocated (gib) | Reserved (gib) |
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|:-------------:|:------:|:----:|:---------------:|:------:|:------------:|:---------------:|:--------------:|
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| No log | 0 | 0 | 0.2049 | 1.2275 | 27.41 | 27.41 | 30.62 |
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| 0.2339 | 0.5 | 120 | 0.2288 | 1.2571 | 34.91 | 34.91 | 59.04 |
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| 0.2290 | 1.0 | 240 | 0.2166 | 1.2419 | 34.91 | 34.91 | 57.54 |
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| 0.0898 | 1.5 | 360 | 0.2251 | 1.2524 | 34.91 | 34.91 | 57.54 |
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| 0.1331 | 1.9917 | 478 | 0.2227 | 1.2494 | 34.91 | 34.91 | 57.25 |
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### Framework versions
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- Transformers 5.5.4
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- Pytorch 2.10.0+cu128
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- Datasets 4.8.4
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- Tokenizers 0.22.2
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