Training in progress, step 100

.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.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,161 @@
+---
+library_name: peft
+license: mit
+base_model: FacebookAI/xlm-roberta-large
+tags:
+- generated_from_trainer
+datasets:
+- conll2002
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: roberta-large-ner-qlorafinetune-runs-colab
+  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. -->
+
+# roberta-large-ner-qlorafinetune-runs-colab
+
+This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the conll2002 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0861
+- Precision: 0.8792
+- Recall: 0.8860
+- F1: 0.8826
+- Accuracy: 0.9817
+
+## 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: 0.0004
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- training_steps: 1820
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 1.1639        | 0.0766 | 20   | 0.4142          | 0.1415    | 0.0533 | 0.0774 | 0.8637   |
+| 0.2638        | 0.1533 | 40   | 0.2052          | 0.5873    | 0.6105 | 0.5987 | 0.9471   |
+| 0.1538        | 0.2299 | 60   | 0.1406          | 0.7147    | 0.7229 | 0.7188 | 0.9620   |
+| 0.1021        | 0.3065 | 80   | 0.1212          | 0.7429    | 0.7847 | 0.7632 | 0.9682   |
+| 0.1142        | 0.3831 | 100  | 0.1146          | 0.7883    | 0.7930 | 0.7906 | 0.9714   |
+| 0.0836        | 0.4598 | 120  | 0.1066          | 0.8086    | 0.8263 | 0.8174 | 0.9741   |
+| 0.0816        | 0.5364 | 140  | 0.0810          | 0.8441    | 0.8463 | 0.8452 | 0.9786   |
+| 0.0867        | 0.6130 | 160  | 0.0784          | 0.8462    | 0.8557 | 0.8509 | 0.9786   |
+| 0.0697        | 0.6897 | 180  | 0.0853          | 0.8248    | 0.8339 | 0.8293 | 0.9765   |
+| 0.0719        | 0.7663 | 200  | 0.0755          | 0.8433    | 0.8555 | 0.8493 | 0.9795   |
+| 0.0584        | 0.8429 | 220  | 0.0718          | 0.8492    | 0.8693 | 0.8591 | 0.9805   |
+| 0.0553        | 0.9195 | 240  | 0.0792          | 0.8399    | 0.8580 | 0.8488 | 0.9775   |
+| 0.049         | 0.9962 | 260  | 0.0748          | 0.8462    | 0.8725 | 0.8591 | 0.9798   |
+| 0.0458        | 1.0728 | 280  | 0.0820          | 0.8180    | 0.8532 | 0.8352 | 0.9777   |
+| 0.049         | 1.1494 | 300  | 0.0818          | 0.8490    | 0.8672 | 0.8580 | 0.9784   |
+| 0.0521        | 1.2261 | 320  | 0.0757          | 0.8626    | 0.8727 | 0.8676 | 0.9795   |
+| 0.0492        | 1.3027 | 340  | 0.0828          | 0.8284    | 0.8552 | 0.8416 | 0.9776   |
+| 0.0517        | 1.3793 | 360  | 0.0808          | 0.8409    | 0.8523 | 0.8465 | 0.9780   |
+| 0.0464        | 1.4559 | 380  | 0.0852          | 0.8385    | 0.8509 | 0.8447 | 0.9772   |
+| 0.0487        | 1.5326 | 400  | 0.0761          | 0.8573    | 0.8656 | 0.8614 | 0.9782   |
+| 0.0517        | 1.6092 | 420  | 0.0714          | 0.8403    | 0.8624 | 0.8512 | 0.9796   |
+| 0.0587        | 1.6858 | 440  | 0.0700          | 0.8398    | 0.8603 | 0.8499 | 0.9806   |
+| 0.0541        | 1.7625 | 460  | 0.0665          | 0.8679    | 0.8844 | 0.8761 | 0.9814   |
+| 0.0459        | 1.8391 | 480  | 0.0677          | 0.8653    | 0.8736 | 0.8694 | 0.9807   |
+| 0.0494        | 1.9157 | 500  | 0.0633          | 0.8707    | 0.8819 | 0.8763 | 0.9817   |
+| 0.0412        | 1.9923 | 520  | 0.0717          | 0.8552    | 0.8660 | 0.8606 | 0.9801   |
+| 0.048         | 2.0690 | 540  | 0.0735          | 0.8642    | 0.8757 | 0.8699 | 0.9797   |
+| 0.0343        | 2.1456 | 560  | 0.0721          | 0.8574    | 0.8690 | 0.8632 | 0.9799   |
+| 0.0276        | 2.2222 | 580  | 0.0784          | 0.8438    | 0.8612 | 0.8524 | 0.9800   |
+| 0.0376        | 2.2989 | 600  | 0.0758          | 0.8459    | 0.8631 | 0.8544 | 0.9787   |
+| 0.0334        | 2.3755 | 620  | 0.0736          | 0.8474    | 0.8578 | 0.8526 | 0.9791   |
+| 0.0342        | 2.4521 | 640  | 0.0681          | 0.8523    | 0.8789 | 0.8654 | 0.9813   |
+| 0.0325        | 2.5287 | 660  | 0.0708          | 0.8771    | 0.8837 | 0.8804 | 0.9814   |
+| 0.0319        | 2.6054 | 680  | 0.0822          | 0.8703    | 0.8729 | 0.8716 | 0.9793   |
+| 0.0376        | 2.6820 | 700  | 0.0733          | 0.8622    | 0.8727 | 0.8674 | 0.9793   |
+| 0.034         | 2.7586 | 720  | 0.0686          | 0.8808    | 0.8867 | 0.8838 | 0.9825   |
+| 0.0342        | 2.8352 | 740  | 0.0693          | 0.8654    | 0.8819 | 0.8736 | 0.9813   |
+| 0.0334        | 2.9119 | 760  | 0.0718          | 0.8686    | 0.8867 | 0.8775 | 0.9813   |
+| 0.0366        | 2.9885 | 780  | 0.0661          | 0.8775    | 0.8888 | 0.8831 | 0.9823   |
+| 0.0433        | 3.0651 | 800  | 0.0785          | 0.8434    | 0.8787 | 0.8607 | 0.9805   |
+| 0.0257        | 3.1418 | 820  | 0.0773          | 0.8705    | 0.8759 | 0.8732 | 0.9805   |
+| 0.0264        | 3.2184 | 840  | 0.0791          | 0.8736    | 0.8812 | 0.8774 | 0.9801   |
+| 0.0256        | 3.2950 | 860  | 0.0756          | 0.8591    | 0.8716 | 0.8653 | 0.9801   |
+| 0.0229        | 3.3716 | 880  | 0.0751          | 0.8656    | 0.8748 | 0.8702 | 0.9801   |
+| 0.0276        | 3.4483 | 900  | 0.0808          | 0.8440    | 0.8665 | 0.8551 | 0.9775   |
+| 0.0374        | 3.5249 | 920  | 0.0685          | 0.8824    | 0.8899 | 0.8862 | 0.9820   |
+| 0.0243        | 3.6015 | 940  | 0.0738          | 0.8776    | 0.8863 | 0.8819 | 0.9817   |
+| 0.027         | 3.6782 | 960  | 0.0741          | 0.8761    | 0.8835 | 0.8798 | 0.9813   |
+| 0.0225        | 3.7548 | 980  | 0.0674          | 0.8895    | 0.9012 | 0.8953 | 0.9830   |
+| 0.0285        | 3.8314 | 1000 | 0.0702          | 0.8801    | 0.8886 | 0.8843 | 0.9827   |
+| 0.0251        | 3.9080 | 1020 | 0.0745          | 0.8767    | 0.8842 | 0.8804 | 0.9810   |
+| 0.0297        | 3.9847 | 1040 | 0.0713          | 0.8782    | 0.8867 | 0.8825 | 0.9820   |
+| 0.0177        | 4.0613 | 1060 | 0.0805          | 0.8784    | 0.8851 | 0.8818 | 0.9814   |
+| 0.0211        | 4.1379 | 1080 | 0.0842          | 0.8802    | 0.8812 | 0.8807 | 0.9812   |
+| 0.0182        | 4.2146 | 1100 | 0.0771          | 0.8747    | 0.8874 | 0.8810 | 0.9814   |
+| 0.0187        | 4.2912 | 1120 | 0.0844          | 0.8737    | 0.8851 | 0.8794 | 0.9813   |
+| 0.017         | 4.3678 | 1140 | 0.0779          | 0.8834    | 0.8929 | 0.8881 | 0.9822   |
+| 0.0203        | 4.4444 | 1160 | 0.0806          | 0.8798    | 0.8913 | 0.8855 | 0.9822   |
+| 0.0176        | 4.5211 | 1180 | 0.0839          | 0.8740    | 0.8865 | 0.8802 | 0.9804   |
+| 0.0168        | 4.5977 | 1200 | 0.0862          | 0.8759    | 0.8835 | 0.8797 | 0.9809   |
+| 0.0199        | 4.6743 | 1220 | 0.0795          | 0.8747    | 0.8869 | 0.8808 | 0.9819   |
+| 0.0238        | 4.7510 | 1240 | 0.0785          | 0.8680    | 0.8782 | 0.8731 | 0.9807   |
+| 0.0204        | 4.8276 | 1260 | 0.0775          | 0.8638    | 0.8741 | 0.8689 | 0.9800   |
+| 0.0205        | 4.9042 | 1280 | 0.0770          | 0.8699    | 0.8805 | 0.8752 | 0.9813   |
+| 0.0161        | 4.9808 | 1300 | 0.0764          | 0.8744    | 0.8817 | 0.8780 | 0.9813   |
+| 0.0145        | 5.0575 | 1320 | 0.0794          | 0.8755    | 0.8874 | 0.8814 | 0.9817   |
+| 0.0124        | 5.1341 | 1340 | 0.0790          | 0.8851    | 0.8886 | 0.8868 | 0.9823   |
+| 0.016         | 5.2107 | 1360 | 0.0818          | 0.8823    | 0.8890 | 0.8857 | 0.9815   |
+| 0.0151        | 5.2874 | 1380 | 0.0806          | 0.8844    | 0.8879 | 0.8861 | 0.9823   |
+| 0.0112        | 5.3640 | 1400 | 0.0833          | 0.8784    | 0.8844 | 0.8814 | 0.9813   |
+| 0.0141        | 5.4406 | 1420 | 0.0841          | 0.8805    | 0.8840 | 0.8822 | 0.9810   |
+| 0.0137        | 5.5172 | 1440 | 0.0851          | 0.8850    | 0.8879 | 0.8864 | 0.9822   |
+| 0.0167        | 5.5939 | 1460 | 0.0830          | 0.8807    | 0.8853 | 0.8830 | 0.9816   |
+| 0.0154        | 5.6705 | 1480 | 0.0808          | 0.8721    | 0.8819 | 0.8770 | 0.9810   |
+| 0.0114        | 5.7471 | 1500 | 0.0816          | 0.8816    | 0.8897 | 0.8856 | 0.9820   |
+| 0.0123        | 5.8238 | 1520 | 0.0832          | 0.8769    | 0.8835 | 0.8802 | 0.9814   |
+| 0.0151        | 5.9004 | 1540 | 0.0863          | 0.8735    | 0.8778 | 0.8756 | 0.9807   |
+| 0.0113        | 5.9770 | 1560 | 0.0874          | 0.8719    | 0.8805 | 0.8762 | 0.9807   |
+| 0.0076        | 6.0536 | 1580 | 0.0896          | 0.8763    | 0.8826 | 0.8795 | 0.9814   |
+| 0.0098        | 6.1303 | 1600 | 0.0880          | 0.8838    | 0.8876 | 0.8857 | 0.9819   |
+| 0.0104        | 6.2069 | 1620 | 0.0887          | 0.8760    | 0.8812 | 0.8786 | 0.9807   |
+| 0.0108        | 6.2835 | 1640 | 0.0854          | 0.8773    | 0.8837 | 0.8805 | 0.9815   |
+| 0.0116        | 6.3602 | 1660 | 0.0830          | 0.8837    | 0.8888 | 0.8862 | 0.9820   |
+| 0.0105        | 6.4368 | 1680 | 0.0838          | 0.8827    | 0.8890 | 0.8859 | 0.9820   |
+| 0.0092        | 6.5134 | 1700 | 0.0847          | 0.8794    | 0.8879 | 0.8836 | 0.9817   |
+| 0.0105        | 6.5900 | 1720 | 0.0842          | 0.8778    | 0.8865 | 0.8821 | 0.9819   |
+| 0.0114        | 6.6667 | 1740 | 0.0847          | 0.8802    | 0.8863 | 0.8832 | 0.9818   |
+| 0.0089        | 6.7433 | 1760 | 0.0851          | 0.8794    | 0.8865 | 0.8829 | 0.9819   |
+| 0.0104        | 6.8199 | 1780 | 0.0861          | 0.8797    | 0.8856 | 0.8826 | 0.9816   |
+| 0.0099        | 6.8966 | 1800 | 0.0863          | 0.8804    | 0.8860 | 0.8832 | 0.9816   |
+| 0.0078        | 6.9732 | 1820 | 0.0861          | 0.8792    | 0.8860 | 0.8826 | 0.9817   |
+
+
+### Framework versions
+
+- PEFT 0.13.2
+- Transformers 4.47.0
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "FacebookAI/xlm-roberta-large",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 64,
+  "lora_dropout": 0.0,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": [
+    "classifier",
+    "score"
+  ],
+  "peft_type": "LORA",
+  "r": 256,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query",
+    "key",
+    "dense",
+    "value"
+  ],
+  "task_type": "TOKEN_CLS",
+  "use_dora": false,
+  "use_rslora": false
+}

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special_tokens_map.json

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+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "mask_token": {
+    "content": "<mask>",
+    "lstrip": true,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "unk_token": "<unk>"
+}

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tokenizer_config.json

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+  "added_tokens_decoder": {
+    "0": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "rstrip": false,
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+  "clean_up_tokenization_spaces": false,
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+  "extra_special_tokens": {},
+  "mask_token": "<mask>",
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+  "sep_token": "</s>",
+  "tokenizer_class": "XLMRobertaTokenizer",
+  "unk_token": "<unk>"
+}

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