End of training

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-multilingual-cased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: spa-eng-pos-tagging-v6
+  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. -->
+
+# spa-eng-pos-tagging-v6
+
+This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3128
+- Accuracy: 0.9056
+- Precision: 0.9032
+- Recall: 0.8293
+- F1: 0.8345
+- Hamming Loss: 0.0944
+
+## 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: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 14
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     | Hamming Loss |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|:------------:|
+| 1.0141        | 1.0   | 1744  | 0.7804          | 0.7158   | 0.7328    | 0.6183 | 0.6345 | 0.2842       |
+| 0.6292        | 2.0   | 3488  | 0.5384          | 0.7973   | 0.8111    | 0.7029 | 0.7213 | 0.2027       |
+| 0.4438        | 3.0   | 5232  | 0.4236          | 0.8462   | 0.8346    | 0.7762 | 0.7732 | 0.1538       |
+| 0.3626        | 4.0   | 6976  | 0.3856          | 0.8651   | 0.8524    | 0.7933 | 0.7903 | 0.1349       |
+| 0.3141        | 5.0   | 8720  | 0.3697          | 0.8712   | 0.8688    | 0.7998 | 0.8028 | 0.1288       |
+| 0.2575        | 6.0   | 10464 | 0.3689          | 0.8751   | 0.8758    | 0.8003 | 0.8058 | 0.1249       |
+| 0.2117        | 7.0   | 12208 | 0.3329          | 0.8890   | 0.8832    | 0.8169 | 0.8184 | 0.1110       |
+| 0.1864        | 8.0   | 13952 | 0.3235          | 0.9010   | 0.8946    | 0.8278 | 0.8293 | 0.0990       |
+| 0.1555        | 9.0   | 15696 | 0.3128          | 0.9056   | 0.9032    | 0.8293 | 0.8345 | 0.0944       |
+| 0.1322        | 10.0  | 17440 | 0.3311          | 0.9088   | 0.9010    | 0.8376 | 0.8377 | 0.0912       |
+| 0.1111        | 11.0  | 19184 | 0.3394          | 0.9101   | 0.9081    | 0.8319 | 0.8383 | 0.0899       |
+| 0.0874        | 12.0  | 20928 | 0.3472          | 0.9148   | 0.9100    | 0.8407 | 0.8440 | 0.0852       |
+| 0.0659        | 13.0  | 22672 | 0.3635          | 0.9131   | 0.9072    | 0.8400 | 0.8422 | 0.0869       |
+| 0.0608        | 14.0  | 24416 | 0.3560          | 0.9187   | 0.9140    | 0.8452 | 0.8482 | 0.0813       |
+
+
+### Framework versions
+
+- Transformers 4.32.0
+- Pytorch 2.0.1+cu118
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "distilbert-base-multilingual-cased",
+  "activation": "gelu",
+  "architectures": [
+    "BertForTokenClassification"
+  ],
+  "attention_dropout": 0.1,
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dim": 3072,
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
+    "4": "LABEL_4",
+    "5": "LABEL_5",
+    "6": "LABEL_6",
+    "7": "LABEL_7",
+    "8": "LABEL_8",
+    "9": "LABEL_9",
+    "10": "LABEL_10",
+    "11": "LABEL_11",
+    "12": "LABEL_12",
+    "13": "LABEL_13",
+    "14": "LABEL_14",
+    "15": "LABEL_15",
+    "16": "LABEL_16"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_10": 10,
+    "LABEL_11": 11,
+    "LABEL_12": 12,
+    "LABEL_13": 13,
+    "LABEL_14": 14,
+    "LABEL_15": 15,
+    "LABEL_16": 16,
+    "LABEL_2": 2,
+    "LABEL_3": 3,
+    "LABEL_4": 4,
+    "LABEL_5": 5,
+    "LABEL_6": 6,
+    "LABEL_7": 7,
+    "LABEL_8": 8,
+    "LABEL_9": 9
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "n_heads": 12,
+  "n_layers": 6,
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": false,
+  "tie_weights_": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.32.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 119547
+}

pytorch_model.bin

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training_args.bin

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