WNUT 17 training

README.md

@@ -1,3 +1,89 @@
 ---
 license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- wnut_17
+model-index:
+- name: fine_tune_bert_output
+  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. -->
+
+# fine_tune_bert_output
+
+This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) on the wnut_17 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3504
+- Overall Precision: 0.6850
+- Overall Recall: 0.6196
+- Overall F1: 0.6507
+- Overall Accuracy: 0.9502
+- Corporation F1: 0.2626
+- Creative-work F1: 0.4460
+- Group F1: 0.3692
+- Location F1: 0.7283
+- Person F1: 0.7928
+- Product F1: 0.3852
+
+## 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: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 100
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Corporation F1 | Creative-work F1 | Group F1 | Location F1 | Person F1 | Product F1 |
+|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:--------------:|:----------------:|:--------:|:-----------:|:---------:|:----------:|
+| 0.2954        | 1.0   | 213  | 0.4357          | 0.0               | 0.0            | 0.0        | 0.8979           | 0.0            | 0.0              | 0.0      | 0.0         | 0.0       | 0.0        |
+| 0.1654        | 2.0   | 426  | 0.3435          | 0.5890            | 0.3929         | 0.4714     | 0.9307           | 0.0            | 0.0              | 0.0      | 0.4444      | 0.6181    | 0.0        |
+| 0.1213        | 3.0   | 639  | 0.2981          | 0.6425            | 0.4776         | 0.5479     | 0.9380           | 0.1961         | 0.0565           | 0.1720   | 0.5507      | 0.7285    | 0.0        |
+| 0.051         | 4.0   | 852  | 0.2958          | 0.7020            | 0.4892         | 0.5766     | 0.9430           | 0.2540         | 0.3458           | 0.2157   | 0.63        | 0.73      | 0.2388     |
+| 0.0503        | 5.0   | 1065 | 0.3154          | 0.6659            | 0.5033         | 0.5733     | 0.9429           | 0.2373         | 0.3365           | 0.3212   | 0.6         | 0.7223    | 0.2896     |
+| 0.026         | 6.0   | 1278 | 0.2787          | 0.6768            | 0.5706         | 0.6192     | 0.9479           | 0.256          | 0.4163           | 0.3699   | 0.7107      | 0.7717    | 0.3052     |
+| 0.0271        | 7.0   | 1491 | 0.2940          | 0.7122            | 0.5714         | 0.6341     | 0.9486           | 0.25           | 0.3982           | 0.3676   | 0.7033      | 0.7717    | 0.3460     |
+| 0.0239        | 8.0   | 1704 | 0.2872          | 0.6210            | 0.5839         | 0.6019     | 0.9461           | 0.2722         | 0.4188           | 0.2902   | 0.7389      | 0.7593    | 0.3597     |
+| 0.0155        | 9.0   | 1917 | 0.2910          | 0.6863            | 0.5905         | 0.6348     | 0.9494           | 0.2623         | 0.4959           | 0.3433   | 0.6878      | 0.7708    | 0.3614     |
+| 0.0122        | 10.0  | 2130 | 0.3067          | 0.6966            | 0.5797         | 0.6328     | 0.9490           | 0.2558         | 0.4609           | 0.3309   | 0.6842      | 0.7645    | 0.3835     |
+| 0.0161        | 11.0  | 2343 | 0.2782          | 0.6637            | 0.6096         | 0.6355     | 0.9502           | 0.3103         | 0.4710           | 0.4275   | 0.6811      | 0.7688    | 0.4110     |
+| 0.0232        | 12.0  | 2556 | 0.3123          | 0.6832            | 0.5822         | 0.6287     | 0.9495           | 0.3235         | 0.4722           | 0.4      | 0.7374      | 0.7568    | 0.4321     |
+| 0.012         | 13.0  | 2769 | 0.3161          | 0.6663            | 0.5573         | 0.6070     | 0.9475           | 0.2128         | 0.4474           | 0.3289   | 0.7243      | 0.7400    | 0.4130     |
+| 0.0051        | 14.0  | 2982 | 0.3241          | 0.7131            | 0.5864         | 0.6436     | 0.9498           | 0.3125         | 0.4839           | 0.3934   | 0.6952      | 0.7700    | 0.3802     |
+| 0.0096        | 15.0  | 3195 | 0.3140          | 0.6924            | 0.6321         | 0.6609     | 0.9520           | 0.3036         | 0.4542           | 0.3576   | 0.7312      | 0.7953    | 0.432      |
+| 0.0045        | 16.0  | 3408 | 0.3356          | 0.6917            | 0.6038         | 0.6448     | 0.9498           | 0.2899         | 0.4858           | 0.3582   | 0.6952      | 0.7840    | 0.4275     |
+| 0.0066        | 17.0  | 3621 | 0.3308          | 0.6738            | 0.6262         | 0.6492     | 0.9510           | 0.2957         | 0.4333           | 0.3673   | 0.6989      | 0.7954    | 0.3320     |
+| 0.0068        | 18.0  | 3834 | 0.3527          | 0.7157            | 0.6063         | 0.6565     | 0.9505           | 0.2353         | 0.4211           | 0.4058   | 0.7182      | 0.7991    | 0.3825     |
+| 0.0033        | 19.0  | 4047 | 0.3522          | 0.7298            | 0.6013         | 0.6594     | 0.9514           | 0.2093         | 0.4454           | 0.4390   | 0.7006      | 0.7912    | 0.4000     |
+| 0.0067        | 20.0  | 4260 | 0.3721          | 0.6859            | 0.5839         | 0.6308     | 0.9476           | 0.2774         | 0.3442           | 0.3881   | 0.7254      | 0.7844    | 0.3140     |
+| 0.0083        | 21.0  | 4473 | 0.3504          | 0.6850            | 0.6196         | 0.6507     | 0.9502           | 0.2626         | 0.4460           | 0.3692   | 0.7283      | 0.7928    | 0.3852     |
+
+
+### Framework versions
+
+- Transformers 4.17.0
+- Pytorch 1.11.0+cu113
+- Datasets 2.0.0
+- Tokenizers 0.11.6
+

added_tokens.json

@@ -0,0 +1 @@
+{"<mask>": 64000}

all_results.json

@@ -0,0 +1,32 @@
+{
+    "epoch": 21.0,
+    "total_flos": 1641754006788696.0,
+    "train_corporation_f1": 0.9816971713810316,
+    "train_creative-work_f1": 0.9383886255924171,
+    "train_group_f1": 0.9757343550447,
+    "train_location_f1": 0.9845758354755784,
+    "train_loss": 0.008754712529480457,
+    "train_overall_accuracy": 0.9985107796641235,
+    "train_overall_f1": 0.9778966131907308,
+    "train_overall_precision": 0.9723502304147466,
+    "train_overall_recall": 0.9835066332018645,
+    "train_person_f1": 0.9893795416433762,
+    "train_product_f1": 0.9455337690631808,
+    "train_runtime": 16.7057,
+    "train_samples_per_second": 203.164,
+    "train_steps_per_second": 12.75,
+    "validation_corporation_f1": 0.3103448275862069,
+    "validation_creative-work_f1": 0.47104247104247104,
+    "validation_group_f1": 0.42748091603053434,
+    "validation_location_f1": 0.6810810810810811,
+    "validation_loss": 0.2782056927680969,
+    "validation_overall_accuracy": 0.9502437284508382,
+    "validation_overall_f1": 0.6354978354978356,
+    "validation_overall_precision": 0.6636528028933092,
+    "validation_overall_recall": 0.6096345514950167,
+    "validation_person_f1": 0.7687548337200311,
+    "validation_product_f1": 0.4110429447852761,
+    "validation_runtime": 6.5808,
+    "validation_samples_per_second": 153.325,
+    "validation_steps_per_second": 9.725
+}

config.json

@@ -0,0 +1,59 @@
+{
+  "_name_or_path": "/home/jupyter/bertweet-base",
+  "architectures": [
+    "RobertaForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "O",
+    "1": "B-corporation",
+    "2": "I-corporation",
+    "3": "B-creative-work",
+    "4": "I-creative-work",
+    "5": "B-group",
+    "6": "I-group",
+    "7": "B-location",
+    "8": "I-location",
+    "9": "B-person",
+    "10": "I-person",
+    "11": "B-product",
+    "12": "I-product"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_10": 10,
+    "LABEL_11": 11,
+    "LABEL_12": 12,
+    "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-05,
+  "max_position_embeddings": 130,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "tokenizer_class": "BertweetTokenizer",
+  "torch_dtype": "float32",
+  "transformers_version": "4.17.0",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 64001
+}

pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f8c03ec350e0b96e236fd640760bc89a45c2e3627b25d849d74254945c595857
+size 537360049

special_tokens_map.json

@@ -0,0 +1 @@
+{"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "pad_token": "<pad>", "cls_token": "<s>", "mask_token": "<mask>"}

tokenizer_config.json

@@ -0,0 +1 @@
+{"normalization": false, "bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": "<mask>", "special_tokens_map_file": null, "name_or_path": "/home/jupyter/bertweet-base", "tokenizer_class": "BertweetTokenizer"}

training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:259a9221284a45586f6726c8755c0afe9082933f4b71b4bec61c9f3dbafca40c
+size 3055