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ondevicellm
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tinyllama_mole_sft_router05_lr1e-4_ep3

Text Generation
Transformers
TensorBoard
Safetensors
mixtralmole
alignment-handbook
trl
sft
Generated from Trainer
conversational
custom_code
Model card Files
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Files changed (9) hide show
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  2. all_results.json +13 -0
  3. eval_results.json +8 -0
  4. generation_config.json +7 -0
  5. model.safetensors +1 -1
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  7. runs/Feb01_15-59-46_main1/events.out.tfevents.1706852763.main1.95696.1 +3 -0
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1
+ ---
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+ base_model: ondevicellm/tinyllama_mole_v1
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+ tags:
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+ - trl
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+ - sft
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+ - generated_from_trainer
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+ datasets:
8
+ - generator
9
+ model-index:
10
+ - name: tinyllama_mole_sft_router05_lr1e-4_ep3
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+ results: []
12
+ ---
13
+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
15
+ should probably proofread and complete it, then remove this comment. -->
16
+
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+ # tinyllama_mole_sft_router05_lr1e-4_ep3
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+
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+ This model is a fine-tuned version of [ondevicellm/tinyllama_mole_v1](https://huggingface.co/ondevicellm/tinyllama_mole_v1) on the generator dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.1035
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+
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+ ## Model description
24
+
25
+ More information needed
26
+
27
+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
34
+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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+ - train_batch_size: 16
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - distributed_type: multi-GPU
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+ - num_devices: 4
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 128
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+ - total_eval_batch_size: 32
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_steps: 120
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+ - num_epochs: 3
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 2.1588 | 0.61 | 700 | 2.1645 |
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+ | 2.145 | 0.7 | 800 | 2.1567 |
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+ | 2.1366 | 0.79 | 900 | 2.1507 |
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+ | 2.1219 | 0.88 | 1000 | 2.1450 |
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+ | 2.1415 | 0.96 | 1100 | 2.1387 |
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+ | 1.9765 | 1.05 | 1200 | 2.1446 |
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+ | 1.9837 | 1.14 | 1300 | 2.1430 |
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+ | 1.9952 | 1.23 | 1400 | 2.1388 |
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+ | 1.9868 | 1.31 | 1500 | 2.1351 |
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+ | 1.9864 | 1.4 | 1600 | 2.1316 |
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+ | 1.987 | 1.49 | 1700 | 2.1263 |
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+ | 1.9827 | 1.66 | 1900 | 2.1164 |
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+ | 1.9694 | 1.84 | 2100 | 2.1068 |
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+ | 1.9429 | 1.93 | 2200 | 2.1035 |
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+ | 1.8079 | 2.01 | 2300 | 2.1369 |
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+ | 1.8132 | 2.1 | 2400 | 2.1375 |
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+ | 1.8043 | 2.19 | 2500 | 2.1360 |
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+ | 1.7927 | 2.28 | 2600 | 2.1334 |
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+ | 1.8015 | 2.98 | 3400 | 2.1283 |
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+
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+
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+ ### Framework versions
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