End of training

README.md

@@ -1,201 +1,76 @@
 ---
-library_name: transformers
-tags: []
+license: mit
+base_model: facebook/w2v-bert-2.0
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: w2v-bert-2.0-classical-latin
+  results: []
 ---
 
-# Model Card for Model ID
+<!-- 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. -->
 
-<!-- Provide a quick summary of what the model is/does. -->
+# w2v-bert-2.0-classical-latin
 
+This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5026
+- Wer: 0.1651
 
+## Model description
 
-## Model Details
+More information needed
 
-### Model Description
+## Intended uses & limitations
 
-<!-- Provide a longer summary of what this model is. -->
+More information needed
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+## Training and evaluation data
 
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
+More information needed
 
-### Model Sources [optional]
+## Training procedure
 
-<!-- Provide the basic links for the model. -->
+### Training hyperparameters
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+The following hyperparameters were used during training:
+- learning_rate: 0.0001
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 300
+- num_epochs: 15
+- mixed_precision_training: Native AMP
 
-## Uses
+### Training results
 
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+| Training Loss | Epoch | Step | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 2.9864        | 1.14  | 50   | 2.4639          | 1.0    |
+| 0.7134        | 2.27  | 100  | 0.4891          | 0.3601 |
+| 0.5196        | 3.41  | 150  | 0.5267          | 0.3022 |
+| 0.3779        | 4.55  | 200  | 0.4407          | 0.2369 |
+| 0.3818        | 5.68  | 250  | 0.4516          | 0.2360 |
+| 0.3           | 6.82  | 300  | 0.4365          | 0.2379 |
+| 0.3252        | 7.95  | 350  | 0.4238          | 0.2183 |
+| 0.2736        | 9.09  | 400  | 0.4609          | 0.2034 |
+| 0.1588        | 10.23 | 450  | 0.4007          | 0.2239 |
+| 0.1223        | 11.36 | 500  | 0.4892          | 0.1987 |
+| 0.0859        | 12.5  | 550  | 0.5393          | 0.1772 |
+| 0.0575        | 13.64 | 600  | 0.4629          | 0.1744 |
+| 0.0464        | 14.77 | 650  | 0.5026          | 0.1651 |
 
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
-
-[More Information Needed]
-
-## Training Details
-
-### Training Data
-
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-
-[More Information Needed]
-
-### Training Procedure 
-
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
-#### Training Hyperparameters
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
-
-## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
-
-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Model Card Authors [optional]
-
-[More Information Needed]
-
-## Model Card Contact
-
-[More Information Needed]
 
+### Framework versions
 
+- Transformers 4.38.0
+- Pytorch 2.1.0+cu121
+- Datasets 2.17.1
+- Tokenizers 0.15.2

config.json

@@ -4,12 +4,12 @@
   "adapter_act": "relu",
   "adapter_kernel_size": 3,
   "adapter_stride": 2,
-  "add_adapter": false,
+  "add_adapter": true,
   "apply_spec_augment": false,
   "architectures": [
     "Wav2Vec2BertForCTC"
   ],
-  "attention_dropout": 0.15,
+  "attention_dropout": 0.01,
   "bos_token_id": 1,
   "classifier_proj_size": 768,
   "codevector_dim": 768,
@@ -25,19 +25,19 @@
   "feature_projection_input_dim": 160,
   "final_dropout": 0.1,
   "hidden_act": "swish",
-  "hidden_dropout": 0.15,
+  "hidden_dropout": 0.0,
   "hidden_size": 1024,
   "initializer_range": 0.02,
   "intermediate_size": 4096,
   "layer_norm_eps": 1e-05,
-  "layerdrop": 0.15,
+  "layerdrop": 0.0,
   "left_max_position_embeddings": 64,
   "mask_feature_length": 10,
   "mask_feature_min_masks": 0,
   "mask_feature_prob": 0.0,
   "mask_time_length": 10,
   "mask_time_min_masks": 2,
-  "mask_time_prob": 0.05,
+  "mask_time_prob": 0.0,
   "max_source_positions": 5000,
   "model_type": "wav2vec2-bert",
   "num_adapter_layers": 1,
@@ -47,7 +47,7 @@
   "num_hidden_layers": 24,
   "num_negatives": 100,
   "output_hidden_size": 1024,
-  "pad_token_id": 28,
+  "pad_token_id": 26,
   "position_embeddings_type": "relative_key",
   "proj_codevector_dim": 768,
   "right_max_position_embeddings": 8,
@@ -74,9 +74,9 @@
     1
   ],
   "torch_dtype": "float32",
-  "transformers_version": "4.37.2",
+  "transformers_version": "4.38.0",
   "use_intermediate_ffn_before_adapter": false,
   "use_weighted_layer_sum": false,
-  "vocab_size": 31,
+  "vocab_size": 29,
   "xvector_output_dim": 512
 }

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