End of training

README.md

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+---
+library_name: transformers
+base_model: roneneldan/TinyStories-1M
+tags:
+- generated_from_trainer
+model-index:
+- name: tinylm1M-stella-2sent_32clust-2025-04-04-13-49
+  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. -->
+
+# tinylm1M-stella-2sent_32clust-2025-04-04-13-49
+
+This model is a fine-tuned version of [roneneldan/TinyStories-1M](https://huggingface.co/roneneldan/TinyStories-1M) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.2485
+
+## 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: 5e-06
+- train_batch_size: 4
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 8
+- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch   | Step  | Validation Loss |
+|:-------------:|:-------:|:-----:|:---------------:|
+| 2.603         | 0.8418  | 500   | 2.5493          |
+| 2.5641        | 1.6835  | 1000  | 2.5072          |
+| 2.5856        | 2.5253  | 1500  | 2.4748          |
+| 2.4812        | 3.3670  | 2000  | 2.4526          |
+| 2.3806        | 4.2088  | 2500  | 2.4287          |
+| 2.365         | 5.0505  | 3000  | 2.4067          |
+| 2.3335        | 5.8923  | 3500  | 2.3860          |
+| 2.3483        | 6.7340  | 4000  | 2.3676          |
+| 2.3202        | 7.5758  | 4500  | 2.3528          |
+| 2.3296        | 8.4175  | 5000  | 2.3395          |
+| 2.2774        | 9.2593  | 5500  | 2.3251          |
+| 2.2768        | 10.1010 | 6000  | 2.3136          |
+| 2.312         | 10.9428 | 6500  | 2.3000          |
+| 2.2991        | 11.7845 | 7000  | 2.2903          |
+| 2.3076        | 12.6263 | 7500  | 2.2813          |
+| 2.1882        | 13.4680 | 8000  | 2.2751          |
+| 2.2872        | 14.3098 | 8500  | 2.2669          |
+| 2.3859        | 15.1515 | 9000  | 2.2619          |
+| 2.2089        | 15.9933 | 9500  | 2.2582          |
+| 2.3199        | 16.8350 | 10000 | 2.2533          |
+| 2.1989        | 17.6768 | 10500 | 2.2504          |
+| 2.2267        | 18.5185 | 11000 | 2.2499          |
+| 2.1404        | 19.3603 | 11500 | 2.2485          |
+
+
+### Framework versions
+
+- Transformers 4.50.3
+- Pytorch 2.6.0+cu124
+- Datasets 3.5.0
+- Tokenizers 0.21.1

added_tokens.json

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config.json

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+{
+  "activation_function": "gelu_new",
+  "architectures": [
+    "GPTNeoForCausalLM"
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+  "attention_dropout": 0,
+  "attention_layers": [
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+  "layer_norm_epsilon": 1e-05,
+  "max_position_embeddings": 2048,
+  "model_type": "gpt_neo",
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+  "num_layers": 8,
+  "resid_dropout": 0,
+  "summary_activation": null,
+  "summary_first_dropout": 0.1,
+  "summary_proj_to_labels": true,
+  "summary_type": "cls_index",
+  "summary_use_proj": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.50.3",
+  "use_cache": false,
+  "vocab_size": 50289,
+  "window_size": 256
+}

generation_config.json

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+  "bos_token_id": 50256,
+  "eos_token_id": 50256,
+  "transformers_version": "4.50.3"
+}

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special_tokens_map.json

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tokenizer_config.json

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