End of training

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer_config.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,142 @@
+---
+tags:
+- generated_from_trainer
+model-index:
+- name: t5-base-p-l-akk-en-20240922-080244
+  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. -->
+
+# t5-base-p-l-akk-en-20240922-080244
+
+This model was trained from scratch on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8507
+
+## 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: 3.152142797506865e-05
+- train_batch_size: 12
+- eval_batch_size: 12
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 100
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch   | Step   | Validation Loss |
+|:-------------:|:-------:|:------:|:---------------:|
+| 0.9444        | 1.1384  | 2500   | 0.8638          |
+| 0.8431        | 2.2769  | 5000   | 0.8085          |
+| 0.7912        | 3.4153  | 7500   | 0.7750          |
+| 0.7434        | 4.5537  | 10000  | 0.7531          |
+| 0.7171        | 5.6922  | 12500  | 0.7395          |
+| 0.692         | 6.8306  | 15000  | 0.7278          |
+| 0.6596        | 7.9690  | 17500  | 0.7165          |
+| 0.6155        | 9.1075  | 20000  | 0.7231          |
+| 0.61          | 10.2459 | 22500  | 0.7129          |
+| 0.5886        | 11.3843 | 25000  | 0.7068          |
+| 0.5718        | 12.5228 | 27500  | 0.7084          |
+| 0.5519        | 13.6612 | 30000  | 0.7029          |
+| 0.5412        | 14.7996 | 32500  | 0.7007          |
+| 0.5241        | 15.9381 | 35000  | 0.7017          |
+| 0.5026        | 17.0765 | 37500  | 0.7134          |
+| 0.4733        | 18.2149 | 40000  | 0.7038          |
+| 0.489         | 19.3534 | 42500  | 0.7067          |
+| 0.4666        | 20.4918 | 45000  | 0.7083          |
+| 0.4494        | 21.6302 | 47500  | 0.7061          |
+| 0.4545        | 22.7687 | 50000  | 0.7092          |
+| 0.4357        | 23.9071 | 52500  | 0.7116          |
+| 0.4332        | 25.0455 | 55000  | 0.7189          |
+| 0.4152        | 26.1840 | 57500  | 0.7207          |
+| 0.3995        | 27.3224 | 60000  | 0.7196          |
+| 0.3976        | 28.4608 | 62500  | 0.7184          |
+| 0.3879        | 29.5993 | 65000  | 0.7210          |
+| 0.3812        | 30.7377 | 67500  | 0.7243          |
+| 0.3749        | 31.8761 | 70000  | 0.7241          |
+| 0.3663        | 33.0146 | 72500  | 0.7320          |
+| 0.3612        | 34.1530 | 75000  | 0.7344          |
+| 0.3469        | 35.2914 | 77500  | 0.7377          |
+| 0.3407        | 36.4299 | 80000  | 0.7388          |
+| 0.3309        | 37.5683 | 82500  | 0.7411          |
+| 0.3354        | 38.7067 | 85000  | 0.7354          |
+| 0.3252        | 39.8452 | 87500  | 0.7407          |
+| 0.3167        | 40.9836 | 90000  | 0.7435          |
+| 0.3182        | 42.1220 | 92500  | 0.7502          |
+| 0.2994        | 43.2605 | 95000  | 0.7547          |
+| 0.3064        | 44.3989 | 97500  | 0.7561          |
+| 0.2923        | 45.5373 | 100000 | 0.7529          |
+| 0.2848        | 46.6758 | 102500 | 0.7593          |
+| 0.2843        | 47.8142 | 105000 | 0.7600          |
+| 0.279         | 48.9526 | 107500 | 0.7650          |
+| 0.2781        | 50.0911 | 110000 | 0.7706          |
+| 0.2629        | 51.2295 | 112500 | 0.7730          |
+| 0.2639        | 52.3679 | 115000 | 0.7726          |
+| 0.2624        | 53.5064 | 117500 | 0.7791          |
+| 0.2547        | 54.6448 | 120000 | 0.7776          |
+| 0.2567        | 55.7832 | 122500 | 0.7747          |
+| 0.2484        | 56.9217 | 125000 | 0.7792          |
+| 0.2454        | 58.0601 | 127500 | 0.7893          |
+| 0.2398        | 59.1985 | 130000 | 0.7864          |
+| 0.2313        | 60.3370 | 132500 | 0.7973          |
+| 0.2362        | 61.4754 | 135000 | 0.7964          |
+| 0.2359        | 62.6138 | 137500 | 0.7962          |
+| 0.226         | 63.7523 | 140000 | 0.8009          |
+| 0.2271        | 64.8907 | 142500 | 0.8027          |
+| 0.2249        | 66.0291 | 145000 | 0.8014          |
+| 0.2212        | 67.1676 | 147500 | 0.8077          |
+| 0.2129        | 68.3060 | 150000 | 0.8088          |
+| 0.2131        | 69.4444 | 152500 | 0.8108          |
+| 0.2106        | 70.5829 | 155000 | 0.8144          |
+| 0.2078        | 71.7213 | 157500 | 0.8163          |
+| 0.2103        | 72.8597 | 160000 | 0.8148          |
+| 0.2025        | 73.9982 | 162500 | 0.8215          |
+| 0.2023        | 75.1366 | 165000 | 0.8250          |
+| 0.197         | 76.2750 | 167500 | 0.8267          |
+| 0.1945        | 77.4135 | 170000 | 0.8274          |
+| 0.1919        | 78.5519 | 172500 | 0.8289          |
+| 0.187         | 79.6903 | 175000 | 0.8308          |
+| 0.1948        | 80.8288 | 177500 | 0.8339          |
+| 0.1857        | 81.9672 | 180000 | 0.8346          |
+| 0.191         | 83.1056 | 182500 | 0.8380          |
+| 0.1796        | 84.2441 | 185000 | 0.8387          |
+| 0.1862        | 85.3825 | 187500 | 0.8414          |
+| 0.185         | 86.5209 | 190000 | 0.8409          |
+| 0.1778        | 87.6594 | 192500 | 0.8434          |
+| 0.1824        | 88.7978 | 195000 | 0.8426          |
+| 0.1735        | 89.9362 | 197500 | 0.8443          |
+| 0.1737        | 91.0747 | 200000 | 0.8474          |
+| 0.1787        | 92.2131 | 202500 | 0.8462          |
+| 0.1759        | 93.3515 | 205000 | 0.8484          |
+| 0.1744        | 94.4900 | 207500 | 0.8487          |
+| 0.1778        | 95.6284 | 210000 | 0.8502          |
+| 0.1767        | 96.7668 | 212500 | 0.8507          |
+| 0.175         | 97.9053 | 215000 | 0.8499          |
+| 0.1723        | 99.0437 | 217500 | 0.8507          |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.1+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

config.json

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+  "model_type": "t5",
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+  },
+  "torch_dtype": "float32",
+  "transformers_version": "4.41.2",
+  "use_cache": true,
+  "vocab_size": 122518
+}

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