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Model: joseph-ai/Aris-293M
Source: Original Platform

README.md

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+---
+library_name: transformers
+tags:
+- generated_from_trainer
+model-index:
+- name: Aris-293M
+  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. -->
+
+# Aris-293M
+
+This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 3.2572
+
+## 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: 0.0002
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 2
+- gradient_accumulation_steps: 16
+- total_train_batch_size: 64
+- total_eval_batch_size: 4
+- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 200
+- training_steps: 7630
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 4.8587        | 0.0655 | 500  | 4.8854          |
+| 4.1492        | 0.1311 | 1000 | 4.1392          |
+| 3.8591        | 0.1966 | 1500 | 3.8450          |
+| 3.7696        | 0.2621 | 2000 | 3.6781          |
+| 3.5556        | 0.3277 | 2500 | 3.5741          |
+| 3.5234        | 0.3932 | 3000 | 3.4973          |
+| 3.4189        | 0.4587 | 3500 | 3.4381          |
+| 3.4178        | 0.5242 | 4000 | 3.3871          |
+| 3.3873        | 0.5898 | 4500 | 3.3499          |
+| 3.3054        | 0.6553 | 5000 | 3.3194          |
+| 3.3168        | 0.7208 | 5500 | 3.2948          |
+| 3.2871        | 0.7864 | 6000 | 3.2781          |
+| 3.2399        | 0.8519 | 6500 | 3.2660          |
+| 3.2484        | 0.9174 | 7000 | 3.2593          |
+| 3.2665        | 0.9830 | 7500 | 3.2572          |
+| 3.2976        | 1.0    | 7630 | 3.2572          |
+
+
+### Framework versions
+
+- Transformers 5.12.1
+- Pytorch 2.4.1+cu124
+- Datasets 5.0.0
+- Tokenizers 0.22.2