Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+model-index:
+- name: bert-philosophy-adapted
+  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. -->
+
+# bert-philosophy-adapted
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.5044
+
+## 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-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 500
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step  | Validation Loss |
+|:-------------:|:------:|:-----:|:---------------:|
+| 2.0568        | 0.1020 | 500   | 1.8821          |
+| 1.9169        | 0.2039 | 1000  | 1.7939          |
+| 1.873         | 0.3059 | 1500  | 1.7593          |
+| 1.8408        | 0.4078 | 2000  | 1.7280          |
+| 1.8461        | 0.5098 | 2500  | 1.7069          |
+| 1.8108        | 0.6117 | 3000  | 1.6899          |
+| 1.7959        | 0.7137 | 3500  | 1.6748          |
+| 1.7771        | 0.8157 | 4000  | 1.6490          |
+| 1.7705        | 0.9176 | 4500  | 1.6371          |
+| 1.725         | 1.0196 | 5000  | 1.6317          |
+| 1.707         | 1.1215 | 5500  | 1.6279          |
+| 1.7127        | 1.2235 | 6000  | 1.6100          |
+| 1.6806        | 1.3254 | 6500  | 1.5978          |
+| 1.6809        | 1.4274 | 7000  | 1.5920          |
+| 1.6766        | 1.5294 | 7500  | 1.5831          |
+| 1.6598        | 1.6313 | 8000  | 1.5748          |
+| 1.6632        | 1.7333 | 8500  | 1.5646          |
+| 1.6433        | 1.8352 | 9000  | 1.5554          |
+| 1.6317        | 1.9372 | 9500  | 1.5552          |
+| 1.6141        | 2.0392 | 10000 | 1.5404          |
+| 1.6328        | 2.1411 | 10500 | 1.5393          |
+| 1.5981        | 2.2431 | 11000 | 1.5330          |
+| 1.6192        | 2.3450 | 11500 | 1.5260          |
+| 1.6051        | 2.4470 | 12000 | 1.5198          |
+| 1.6218        | 2.5489 | 12500 | 1.5162          |
+| 1.5721        | 2.6509 | 13000 | 1.5079          |
+| 1.5656        | 2.7529 | 13500 | 1.5109          |
+| 1.5642        | 2.8548 | 14000 | 1.5077          |
+| 1.5715        | 2.9568 | 14500 | 1.5106          |
+
+
+### Framework versions
+
+- Transformers 4.52.4
+- Pytorch 2.6.0+cu124
+- Datasets 3.6.0
+- Tokenizers 0.21.1

all_results.json

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+{
+    "epoch": 3.0,
+    "eval_loss": 1.5044002532958984,
+    "eval_runtime": 68.817,
+    "eval_samples_per_second": 253.353,
+    "eval_steps_per_second": 15.839,
+    "total_flos": 9.67128359434488e+16,
+    "train_loss": 1.7193875008137607,
+    "train_runtime": 8413.0303,
+    "train_samples_per_second": 55.954,
+    "train_steps_per_second": 1.749
+}

eval_results.json

@@ -0,0 +1,7 @@
+{
+    "epoch": 3.0,
+    "eval_loss": 1.5044002532958984,
+    "eval_runtime": 68.817,
+    "eval_samples_per_second": 253.353,
+    "eval_steps_per_second": 15.839
+}

model.safetensors

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+oid sha256:5cb92ab6ced24db9a550e053160dc3631086e89009b61e5c92f3e1789386cf70
 size 438080896

runs/Jun14_19-39-49_8277be47784a/events.out.tfevents.1749938646.8277be47784a.3924.1

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+size 630

train_results.json

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+{
+    "epoch": 3.0,
+    "total_flos": 9.67128359434488e+16,
+    "train_loss": 1.7193875008137607,
+    "train_runtime": 8413.0303,
+    "train_samples_per_second": 55.954,
+    "train_steps_per_second": 1.749
+}