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core-text-cls-data-scientist-salary/10k/fold_0/README.md

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+---
+base_model: intfloat/e5-small-v2
+library_name: peft
+tags:
+- base_model:adapter:intfloat/e5-small-v2
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **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]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### 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
+
+- PEFT 0.18.0

core-text-cls-data-scientist-salary/10k/fold_0/adapter_config.json

@@ -0,0 +1,60 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "BertModel",
+    "parent_library": "transformers.models.bert.modeling_bert"
+  },
+  "base_model_name_or_path": "intfloat/e5-small-v2",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "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": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "encoder.layer.10.intermediate.dense",
+    "encoder.layer.10.attention.self.key",
+    "encoder.layer.9.attention.self.query",
+    "encoder.layer.10.attention.self.value",
+    "encoder.layer.10.attention.self.query",
+    "encoder.layer.11.attention.output.dense",
+    "encoder.layer.11.attention.self.query",
+    "encoder.layer.10.output.dense",
+    "encoder.layer.11.intermediate.dense",
+    "encoder.layer.9.attention.output.dense",
+    "encoder.layer.11.attention.self.value",
+    "encoder.layer.11.output.dense",
+    "encoder.layer.9.intermediate.dense",
+    "encoder.layer.9.attention.self.key",
+    "encoder.layer.10.attention.output.dense",
+    "encoder.layer.9.attention.self.value",
+    "encoder.layer.9.output.dense",
+    "encoder.layer.11.attention.self.key"
+  ],
+  "target_parameters": null,
+  "task_type": null,
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

core-text-cls-data-scientist-salary/10k/fold_0/meta.json

@@ -0,0 +1,59 @@
+{
+  "dataset": "MUL_TEXT_DATA_SCIENTIST_SALARY",
+  "encoder": "e5-small-tar",
+  "model": "intfloat/e5-small-v2",
+  "size": "10k",
+  "fold": 0,
+  "n_train": 10000,
+  "n_test": 5000,
+  "lora": {
+    "learning_rate": 0.0001,
+    "epochs": 50,
+    "lora_rank": 16,
+    "layers": 3,
+    "patience": 3,
+    "weight_decay": 0.001,
+    "batch_size": 256
+  },
+  "best_val_loss": 1.492464303970337,
+  "epochs": 21.0,
+  "n_rows": 15000,
+  "n_inputs": 29490,
+  "n_columns": 6,
+  "features": [
+    "experience",
+    "job_description",
+    "job_desig",
+    "key_skills",
+    "location"
+  ],
+  "finetune_seconds": 1418.8592008799997,
+  "encode_seconds": {
+    "experience": 0.0321362170006978,
+    "job_description": 1.8898558529999718,
+    "job_desig": 2.3539329989998805,
+    "key_skills": 2.6641761460005,
+    "location": 0.32016289700004563
+  },
+  "total_seconds": 1426.1194649920008,
+  "git": "12b5c55",
+  "timestamp": "2026-10-18 09:30:37",
+  "gpu_type": "NVIDIA H100 80GB HBM3",
+  "gpu_total_memory_gb": 79.1787109375,
+  "use_gpu": true,
+  "cpu_cores": 8,
+  "system_ram_gb": 230.04119491577148,
+  "cpu_name": "Intel(R) Xeon(R) Platinum 8481C CPU @ 2.70GHz",
+  "visible_cpus": 8,
+  "ram_limit_gb": 32.0,
+  "expected_hardware": {
+    "gpu_prefix": "NVIDIA A100",
+    "cpu_prefix": null,
+    "cpus": 6,
+    "ram_gb": 32
+  },
+  "official_hardware_mismatches": [
+    "GPU is NVIDIA H100 80GB HBM3, not NVIDIA A100",
+    "8 CPUs are available, not 6"
+  ]
+}

core-text-cls-data-scientist-salary/10k/fold_1/README.md

@@ -0,0 +1,206 @@
+---
+base_model: intfloat/e5-small-v2
+library_name: peft
+tags:
+- base_model:adapter:intfloat/e5-small-v2
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **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]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### 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
+
+- PEFT 0.18.0

core-text-cls-data-scientist-salary/10k/fold_1/adapter_config.json

@@ -0,0 +1,60 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "BertModel",
+    "parent_library": "transformers.models.bert.modeling_bert"
+  },
+  "base_model_name_or_path": "intfloat/e5-small-v2",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "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": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "encoder.layer.11.attention.output.dense",
+    "encoder.layer.10.attention.self.query",
+    "encoder.layer.9.attention.output.dense",
+    "encoder.layer.9.attention.self.value",
+    "encoder.layer.11.intermediate.dense",
+    "encoder.layer.9.intermediate.dense",
+    "encoder.layer.11.attention.self.query",
+    "encoder.layer.9.output.dense",
+    "encoder.layer.10.output.dense",
+    "encoder.layer.11.output.dense",
+    "encoder.layer.11.attention.self.value",
+    "encoder.layer.10.attention.self.key",
+    "encoder.layer.11.attention.self.key",
+    "encoder.layer.9.attention.self.key",
+    "encoder.layer.9.attention.self.query",
+    "encoder.layer.10.intermediate.dense",
+    "encoder.layer.10.attention.output.dense",
+    "encoder.layer.10.attention.self.value"
+  ],
+  "target_parameters": null,
+  "task_type": null,
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

core-text-cls-data-scientist-salary/10k/fold_1/meta.json

@@ -0,0 +1,59 @@
+{
+  "dataset": "MUL_TEXT_DATA_SCIENTIST_SALARY",
+  "encoder": "e5-small-tar",
+  "model": "intfloat/e5-small-v2",
+  "size": "10k",
+  "fold": 1,
+  "n_train": 10000,
+  "n_test": 5000,
+  "lora": {
+    "learning_rate": 0.0001,
+    "epochs": 50,
+    "lora_rank": 16,
+    "layers": 3,
+    "patience": 3,
+    "weight_decay": 0.001,
+    "batch_size": 256
+  },
+  "best_val_loss": 1.5215051174163818,
+  "epochs": 17.0,
+  "n_rows": 15000,
+  "n_inputs": 29485,
+  "n_columns": 6,
+  "features": [
+    "experience",
+    "job_description",
+    "job_desig",
+    "key_skills",
+    "location"
+  ],
+  "finetune_seconds": 1148.4518720370006,
+  "encode_seconds": {
+    "experience": 0.03463212999940879,
+    "job_description": 1.942359622999902,
+    "job_desig": 2.395561735999763,
+    "key_skills": 2.6648438450001777,
+    "location": 0.33051873499971407
+  },
+  "total_seconds": 1155.8197881059996,
+  "git": "12b5c55",
+  "timestamp": "2026-10-18 09:50:08",
+  "gpu_type": "NVIDIA H100 80GB HBM3",
+  "gpu_total_memory_gb": 79.1787109375,
+  "use_gpu": true,
+  "cpu_cores": 8,
+  "system_ram_gb": 230.04119491577148,
+  "cpu_name": "Intel(R) Xeon(R) Platinum 8481C CPU @ 2.70GHz",
+  "visible_cpus": 8,
+  "ram_limit_gb": 32.0,
+  "expected_hardware": {
+    "gpu_prefix": "NVIDIA A100",
+    "cpu_prefix": null,
+    "cpus": 6,
+    "ram_gb": 32
+  },
+  "official_hardware_mismatches": [
+    "GPU is NVIDIA H100 80GB HBM3, not NVIDIA A100",
+    "8 CPUs are available, not 6"
+  ]
+}

core-text-cls-data-scientist-salary/10k/fold_2/README.md

@@ -0,0 +1,206 @@
+---
+base_model: intfloat/e5-small-v2
+library_name: peft
+tags:
+- base_model:adapter:intfloat/e5-small-v2
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **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]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### 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
+
+- PEFT 0.18.0

core-text-cls-data-scientist-salary/10k/fold_2/adapter_config.json

@@ -0,0 +1,60 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "BertModel",
+    "parent_library": "transformers.models.bert.modeling_bert"
+  },
+  "base_model_name_or_path": "intfloat/e5-small-v2",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "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": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "encoder.layer.10.attention.self.value",
+    "encoder.layer.10.attention.self.query",
+    "encoder.layer.10.intermediate.dense",
+    "encoder.layer.11.attention.output.dense",
+    "encoder.layer.9.attention.self.query",
+    "encoder.layer.9.attention.output.dense",
+    "encoder.layer.9.attention.self.key",
+    "encoder.layer.9.output.dense",
+    "encoder.layer.11.attention.self.query",
+    "encoder.layer.11.attention.self.key",
+    "encoder.layer.11.attention.self.value",
+    "encoder.layer.10.attention.output.dense",
+    "encoder.layer.9.attention.self.value",
+    "encoder.layer.9.intermediate.dense",
+    "encoder.layer.11.intermediate.dense",
+    "encoder.layer.11.output.dense",
+    "encoder.layer.10.output.dense",
+    "encoder.layer.10.attention.self.key"
+  ],
+  "target_parameters": null,
+  "task_type": null,
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

core-text-cls-data-scientist-salary/10k/fold_2/meta.json

@@ -0,0 +1,59 @@
+{
+  "dataset": "MUL_TEXT_DATA_SCIENTIST_SALARY",
+  "encoder": "e5-small-tar",
+  "model": "intfloat/e5-small-v2",
+  "size": "10k",
+  "fold": 2,
+  "n_train": 10000,
+  "n_test": 5000,
+  "lora": {
+    "learning_rate": 0.0001,
+    "epochs": 50,
+    "lora_rank": 16,
+    "layers": 3,
+    "patience": 3,
+    "weight_decay": 0.001,
+    "batch_size": 256
+  },
+  "best_val_loss": 1.5151019096374512,
+  "epochs": 17.0,
+  "n_rows": 15000,
+  "n_inputs": 29428,
+  "n_columns": 6,
+  "features": [
+    "experience",
+    "job_description",
+    "job_desig",
+    "key_skills",
+    "location"
+  ],
+  "finetune_seconds": 1148.5763146979998,
+  "encode_seconds": {
+    "experience": 0.03286424399993848,
+    "job_description": 1.902829888999804,
+    "job_desig": 2.339536293000492,
+    "key_skills": 2.639582072999474,
+    "location": 0.32504501799940044
+  },
+  "total_seconds": 1155.816172214999,
+  "git": "12b5c55",
+  "timestamp": "2026-10-18 10:09:39",
+  "gpu_type": "NVIDIA H100 80GB HBM3",
+  "gpu_total_memory_gb": 79.1787109375,
+  "use_gpu": true,
+  "cpu_cores": 8,
+  "system_ram_gb": 230.04119491577148,
+  "cpu_name": "Intel(R) Xeon(R) Platinum 8481C CPU @ 2.70GHz",
+  "visible_cpus": 8,
+  "ram_limit_gb": 32.0,
+  "expected_hardware": {
+    "gpu_prefix": "NVIDIA A100",
+    "cpu_prefix": null,
+    "cpus": 6,
+    "ram_gb": 32
+  },
+  "official_hardware_mismatches": [
+    "GPU is NVIDIA H100 80GB HBM3, not NVIDIA A100",
+    "8 CPUs are available, not 6"
+  ]
+}

core-text-cls-data-scientist-salary/10k/fold_3/README.md

@@ -0,0 +1,206 @@
+---
+base_model: intfloat/e5-small-v2
+library_name: peft
+tags:
+- base_model:adapter:intfloat/e5-small-v2
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **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]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### 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
+
+- PEFT 0.18.0

core-text-cls-data-scientist-salary/10k/fold_3/adapter_config.json

@@ -0,0 +1,60 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "BertModel",
+    "parent_library": "transformers.models.bert.modeling_bert"
+  },
+  "base_model_name_or_path": "intfloat/e5-small-v2",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "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": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "encoder.layer.10.intermediate.dense",
+    "encoder.layer.9.attention.self.key",
+    "encoder.layer.11.attention.self.key",
+    "encoder.layer.9.attention.self.value",
+    "encoder.layer.10.attention.output.dense",
+    "encoder.layer.9.attention.self.query",
+    "encoder.layer.10.attention.self.query",
+    "encoder.layer.11.attention.output.dense",
+    "encoder.layer.10.attention.self.key",
+    "encoder.layer.9.output.dense",
+    "encoder.layer.11.intermediate.dense",
+    "encoder.layer.11.output.dense",
+    "encoder.layer.11.attention.self.value",
+    "encoder.layer.11.attention.self.query",
+    "encoder.layer.10.attention.self.value",
+    "encoder.layer.9.attention.output.dense",
+    "encoder.layer.9.intermediate.dense",
+    "encoder.layer.10.output.dense"
+  ],
+  "target_parameters": null,
+  "task_type": null,
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

core-text-cls-data-scientist-salary/10k/fold_3/meta.json

@@ -0,0 +1,59 @@
+{
+  "dataset": "MUL_TEXT_DATA_SCIENTIST_SALARY",
+  "encoder": "e5-small-tar",
+  "model": "intfloat/e5-small-v2",
+  "size": "10k",
+  "fold": 3,
+  "n_train": 10000,
+  "n_test": 5000,
+  "lora": {
+    "learning_rate": 0.0001,
+    "epochs": 50,
+    "lora_rank": 16,
+    "layers": 3,
+    "patience": 3,
+    "weight_decay": 0.001,
+    "batch_size": 256
+  },
+  "best_val_loss": 1.4985325336456299,
+  "epochs": 27.0,
+  "n_rows": 15000,
+  "n_inputs": 29510,
+  "n_columns": 6,
+  "features": [
+    "experience",
+    "job_description",
+    "job_desig",
+    "key_skills",
+    "location"
+  ],
+  "finetune_seconds": 1823.586081870999,
+  "encode_seconds": {
+    "experience": 0.032067821999589796,
+    "job_description": 1.9071785629985243,
+    "job_desig": 2.363451974999407,
+    "key_skills": 2.6528028009997797,
+    "location": 0.3225891399997636
+  },
+  "total_seconds": 1830.864172171996,
+  "git": "12b5c55",
+  "timestamp": "2026-10-18 10:40:25",
+  "gpu_type": "NVIDIA H100 80GB HBM3",
+  "gpu_total_memory_gb": 79.1787109375,
+  "use_gpu": true,
+  "cpu_cores": 8,
+  "system_ram_gb": 230.04119491577148,
+  "cpu_name": "Intel(R) Xeon(R) Platinum 8481C CPU @ 2.70GHz",
+  "visible_cpus": 8,
+  "ram_limit_gb": 32.0,
+  "expected_hardware": {
+    "gpu_prefix": "NVIDIA A100",
+    "cpu_prefix": null,
+    "cpus": 6,
+    "ram_gb": 32
+  },
+  "official_hardware_mismatches": [
+    "GPU is NVIDIA H100 80GB HBM3, not NVIDIA A100",
+    "8 CPUs are available, not 6"
+  ]
+}

core-text-cls-data-scientist-salary/10k/fold_4/README.md

@@ -0,0 +1,206 @@
+---
+base_model: intfloat/e5-small-v2
+library_name: peft
+tags:
+- base_model:adapter:intfloat/e5-small-v2
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **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]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### 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
+
+- PEFT 0.18.0

core-text-cls-data-scientist-salary/10k/fold_4/adapter_config.json

@@ -0,0 +1,60 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "BertModel",
+    "parent_library": "transformers.models.bert.modeling_bert"
+  },
+  "base_model_name_or_path": "intfloat/e5-small-v2",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "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": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "encoder.layer.9.intermediate.dense",
+    "encoder.layer.11.attention.self.query",
+    "encoder.layer.11.output.dense",
+    "encoder.layer.9.attention.output.dense",
+    "encoder.layer.9.attention.self.key",
+    "encoder.layer.9.output.dense",
+    "encoder.layer.10.attention.self.key",
+    "encoder.layer.10.output.dense",
+    "encoder.layer.10.attention.output.dense",
+    "encoder.layer.10.attention.self.value",
+    "encoder.layer.11.intermediate.dense",
+    "encoder.layer.11.attention.self.key",
+    "encoder.layer.9.attention.self.query",
+    "encoder.layer.10.intermediate.dense",
+    "encoder.layer.9.attention.self.value",
+    "encoder.layer.10.attention.self.query",
+    "encoder.layer.11.attention.self.value",
+    "encoder.layer.11.attention.output.dense"
+  ],
+  "target_parameters": null,
+  "task_type": null,
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

core-text-cls-data-scientist-salary/10k/fold_4/meta.json

@@ -0,0 +1,59 @@
+{
+  "dataset": "MUL_TEXT_DATA_SCIENTIST_SALARY",
+  "encoder": "e5-small-tar",
+  "model": "intfloat/e5-small-v2",
+  "size": "10k",
+  "fold": 4,
+  "n_train": 10000,
+  "n_test": 5000,
+  "lora": {
+    "learning_rate": 0.0001,
+    "epochs": 50,
+    "lora_rank": 16,
+    "layers": 3,
+    "patience": 3,
+    "weight_decay": 0.001,
+    "batch_size": 256
+  },
+  "best_val_loss": 1.5296956300735474,
+  "epochs": 16.0,
+  "n_rows": 15000,
+  "n_inputs": 29500,
+  "n_columns": 6,
+  "features": [
+    "experience",
+    "job_description",
+    "job_desig",
+    "key_skills",
+    "location"
+  ],
+  "finetune_seconds": 1081.6374399289998,
+  "encode_seconds": {
+    "experience": 0.03316083099889511,
+    "job_description": 1.9125347449989931,
+    "job_desig": 2.3436468609997974,
+    "key_skills": 2.6532524230005947,
+    "location": 0.33025668499976746
+  },
+  "total_seconds": 1088.9102914739979,
+  "git": "12b5c55",
+  "timestamp": "2026-10-18 10:58:49",
+  "gpu_type": "NVIDIA H100 80GB HBM3",
+  "gpu_total_memory_gb": 79.1787109375,
+  "use_gpu": true,
+  "cpu_cores": 8,
+  "system_ram_gb": 230.04119491577148,
+  "cpu_name": "Intel(R) Xeon(R) Platinum 8481C CPU @ 2.70GHz",
+  "visible_cpus": 8,
+  "ram_limit_gb": 32.0,
+  "expected_hardware": {
+    "gpu_prefix": "NVIDIA A100",
+    "cpu_prefix": null,
+    "cpus": 6,
+    "ram_gb": 32
+  },
+  "official_hardware_mismatches": [
+    "GPU is NVIDIA H100 80GB HBM3, not NVIDIA A100",
+    "8 CPUs are available, not 6"
+  ]
+}

core-text-cls-data-scientist-salary/10k/fold_5/README.md

@@ -0,0 +1,206 @@
+---
+base_model: intfloat/e5-small-v2
+library_name: peft
+tags:
+- base_model:adapter:intfloat/e5-small-v2
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **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]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### 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
+
+- PEFT 0.18.0

core-text-cls-data-scientist-salary/10k/fold_5/adapter_config.json

@@ -0,0 +1,60 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "BertModel",
+    "parent_library": "transformers.models.bert.modeling_bert"
+  },
+  "base_model_name_or_path": "intfloat/e5-small-v2",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "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": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "encoder.layer.11.intermediate.dense",
+    "encoder.layer.9.attention.self.value",
+    "encoder.layer.11.output.dense",
+    "encoder.layer.10.intermediate.dense",
+    "encoder.layer.9.attention.self.key",
+    "encoder.layer.9.output.dense",
+    "encoder.layer.11.attention.self.key",
+    "encoder.layer.10.attention.self.query",
+    "encoder.layer.9.attention.output.dense",
+    "encoder.layer.10.attention.self.value",
+    "encoder.layer.9.intermediate.dense",
+    "encoder.layer.10.attention.output.dense",
+    "encoder.layer.9.attention.self.query",
+    "encoder.layer.11.attention.output.dense",
+    "encoder.layer.10.attention.self.key",
+    "encoder.layer.11.attention.self.value",
+    "encoder.layer.11.attention.self.query",
+    "encoder.layer.10.output.dense"
+  ],
+  "target_parameters": null,
+  "task_type": null,
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

core-text-cls-data-scientist-salary/10k/fold_5/meta.json

@@ -0,0 +1,59 @@
+{
+  "dataset": "MUL_TEXT_DATA_SCIENTIST_SALARY",
+  "encoder": "e5-small-tar",
+  "model": "intfloat/e5-small-v2",
+  "size": "10k",
+  "fold": 5,
+  "n_train": 10000,
+  "n_test": 5000,
+  "lora": {
+    "learning_rate": 0.0001,
+    "epochs": 50,
+    "lora_rank": 16,
+    "layers": 3,
+    "patience": 3,
+    "weight_decay": 0.001,
+    "batch_size": 256
+  },
+  "best_val_loss": 1.5270895957946777,
+  "epochs": 16.0,
+  "n_rows": 15000,
+  "n_inputs": 29446,
+  "n_columns": 6,
+  "features": [
+    "experience",
+    "job_description",
+    "job_desig",
+    "key_skills",
+    "location"
+  ],
+  "finetune_seconds": 1082.0390864689998,
+  "encode_seconds": {
+    "experience": 0.032966017999569885,
+    "job_description": 1.8922360920005303,
+    "job_desig": 2.331617001000268,
+    "key_skills": 2.6418826850003825,
+    "location": 0.3338915429994813
+  },
+  "total_seconds": 1089.271679808,
+  "git": "12b5c55",
+  "timestamp": "2026-10-18 11:17:13",
+  "gpu_type": "NVIDIA H100 80GB HBM3",
+  "gpu_total_memory_gb": 79.1787109375,
+  "use_gpu": true,
+  "cpu_cores": 8,
+  "system_ram_gb": 230.04119491577148,
+  "cpu_name": "Intel(R) Xeon(R) Platinum 8481C CPU @ 2.70GHz",
+  "visible_cpus": 8,
+  "ram_limit_gb": 32.0,
+  "expected_hardware": {
+    "gpu_prefix": "NVIDIA A100",
+    "cpu_prefix": null,
+    "cpus": 6,
+    "ram_gb": 32
+  },
+  "official_hardware_mismatches": [
+    "GPU is NVIDIA H100 80GB HBM3, not NVIDIA A100",
+    "8 CPUs are available, not 6"
+  ]
+}

core-text-cls-jigsaw-toxicity/10k/fold_0/README.md

@@ -0,0 +1,206 @@
+---
+base_model: intfloat/e5-small-v2
+library_name: peft
+tags:
+- base_model:adapter:intfloat/e5-small-v2
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **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]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### 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
+
+- PEFT 0.18.0

core-text-cls-jigsaw-toxicity/10k/fold_0/adapter_config.json

@@ -0,0 +1,60 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "BertModel",
+    "parent_library": "transformers.models.bert.modeling_bert"
+  },
+  "base_model_name_or_path": "intfloat/e5-small-v2",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "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": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "encoder.layer.11.attention.self.key",
+    "encoder.layer.9.attention.output.dense",
+    "encoder.layer.9.output.dense",
+    "encoder.layer.11.output.dense",
+    "encoder.layer.11.intermediate.dense",
+    "encoder.layer.9.attention.self.value",
+    "encoder.layer.9.attention.self.query",
+    "encoder.layer.10.output.dense",
+    "encoder.layer.10.attention.output.dense",
+    "encoder.layer.11.attention.self.value",
+    "encoder.layer.9.attention.self.key",
+    "encoder.layer.10.intermediate.dense",
+    "encoder.layer.11.attention.self.query",
+    "encoder.layer.10.attention.self.query",
+    "encoder.layer.10.attention.self.key",
+    "encoder.layer.10.attention.self.value",
+    "encoder.layer.9.intermediate.dense",
+    "encoder.layer.11.attention.output.dense"
+  ],
+  "target_parameters": null,
+  "task_type": null,
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

core-text-cls-jigsaw-toxicity/10k/fold_0/meta.json

@@ -0,0 +1,51 @@
+{
+  "dataset": "BIN_TEXT_JIGSAW_TOXICITY",
+  "encoder": "e5-small-tar",
+  "model": "intfloat/e5-small-v2",
+  "size": "10k",
+  "fold": 0,
+  "n_train": 10000,
+  "n_test": 5000,
+  "lora": {
+    "learning_rate": 0.0001,
+    "epochs": 50,
+    "lora_rank": 16,
+    "layers": 3,
+    "patience": 3,
+    "weight_decay": 0.001,
+    "batch_size": 256
+  },
+  "best_val_loss": 0.12114106118679047,
+  "epochs": 20.0,
+  "n_rows": 15000,
+  "n_inputs": 14989,
+  "n_columns": 31,
+  "features": [
+    "comment_text"
+  ],
+  "finetune_seconds": 285.2273222859999,
+  "encode_seconds": {
+    "comment_text": 9.122020795000026
+  },
+  "total_seconds": 294.3493430809999,
+  "git": "12b5c55",
+  "timestamp": "2026-10-18 08:42:25",
+  "gpu_type": "NVIDIA H100 80GB HBM3",
+  "gpu_total_memory_gb": 79.1787109375,
+  "use_gpu": true,
+  "cpu_cores": 8,
+  "system_ram_gb": 230.04119110107422,
+  "cpu_name": "Intel(R) Xeon(R) Platinum 8481C CPU @ 2.70GHz",
+  "visible_cpus": 8,
+  "ram_limit_gb": 32.0,
+  "expected_hardware": {
+    "gpu_prefix": "NVIDIA A100",
+    "cpu_prefix": null,
+    "cpus": 6,
+    "ram_gb": 32
+  },
+  "official_hardware_mismatches": [
+    "GPU is NVIDIA H100 80GB HBM3, not NVIDIA A100",
+    "8 CPUs are available, not 6"
+  ]
+}

core-text-cls-jigsaw-toxicity/10k/fold_1/README.md

@@ -0,0 +1,206 @@
+---
+base_model: intfloat/e5-small-v2
+library_name: peft
+tags:
+- base_model:adapter:intfloat/e5-small-v2
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **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]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### 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
+
+- PEFT 0.18.0

core-text-cls-jigsaw-toxicity/10k/fold_1/adapter_config.json

@@ -0,0 +1,60 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "BertModel",
+    "parent_library": "transformers.models.bert.modeling_bert"
+  },
+  "base_model_name_or_path": "intfloat/e5-small-v2",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "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": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "encoder.layer.9.attention.output.dense",
+    "encoder.layer.11.output.dense",
+    "encoder.layer.9.attention.self.key",
+    "encoder.layer.9.output.dense",
+    "encoder.layer.10.attention.self.value",
+    "encoder.layer.9.intermediate.dense",
+    "encoder.layer.10.attention.self.query",
+    "encoder.layer.10.attention.self.key",
+    "encoder.layer.9.attention.self.value",
+    "encoder.layer.9.attention.self.query",
+    "encoder.layer.11.attention.output.dense",
+    "encoder.layer.10.intermediate.dense",
+    "encoder.layer.11.attention.self.query",
+    "encoder.layer.10.attention.output.dense",
+    "encoder.layer.10.output.dense",
+    "encoder.layer.11.attention.self.value",
+    "encoder.layer.11.intermediate.dense",
+    "encoder.layer.11.attention.self.key"
+  ],
+  "target_parameters": null,
+  "task_type": null,
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

core-text-cls-jigsaw-toxicity/10k/fold_1/meta.json

@@ -0,0 +1,51 @@
+{
+  "dataset": "BIN_TEXT_JIGSAW_TOXICITY",
+  "encoder": "e5-small-tar",
+  "model": "intfloat/e5-small-v2",
+  "size": "10k",
+  "fold": 1,
+  "n_train": 10000,
+  "n_test": 5000,
+  "lora": {
+    "learning_rate": 0.0001,
+    "epochs": 50,
+    "lora_rank": 16,
+    "layers": 3,
+    "patience": 3,
+    "weight_decay": 0.001,
+    "batch_size": 256
+  },
+  "best_val_loss": 0.12573519349098206,
+  "epochs": 14.0,
+  "n_rows": 15000,
+  "n_inputs": 14976,
+  "n_columns": 31,
+  "features": [
+    "comment_text"
+  ],
+  "finetune_seconds": 199.160178224,
+  "encode_seconds": {
+    "comment_text": 8.988780903000134
+  },
+  "total_seconds": 208.14895912700013,
+  "git": "12b5c55",
+  "timestamp": "2026-10-18 08:46:07",
+  "gpu_type": "NVIDIA H100 80GB HBM3",
+  "gpu_total_memory_gb": 79.1787109375,
+  "use_gpu": true,
+  "cpu_cores": 8,
+  "system_ram_gb": 230.04119110107422,
+  "cpu_name": "Intel(R) Xeon(R) Platinum 8481C CPU @ 2.70GHz",
+  "visible_cpus": 8,
+  "ram_limit_gb": 32.0,
+  "expected_hardware": {
+    "gpu_prefix": "NVIDIA A100",
+    "cpu_prefix": null,
+    "cpus": 6,
+    "ram_gb": 32
+  },
+  "official_hardware_mismatches": [
+    "GPU is NVIDIA H100 80GB HBM3, not NVIDIA A100",
+    "8 CPUs are available, not 6"
+  ]
+}

core-text-cls-jigsaw-toxicity/10k/fold_2/README.md

@@ -0,0 +1,206 @@
+---
+base_model: intfloat/e5-small-v2
+library_name: peft
+tags:
+- base_model:adapter:intfloat/e5-small-v2
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **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]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### 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
+
+- PEFT 0.18.0

core-text-cls-jigsaw-toxicity/10k/fold_2/adapter_config.json

@@ -0,0 +1,60 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "BertModel",
+    "parent_library": "transformers.models.bert.modeling_bert"
+  },
+  "base_model_name_or_path": "intfloat/e5-small-v2",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "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": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "encoder.layer.9.attention.output.dense",
+    "encoder.layer.10.attention.self.value",
+    "encoder.layer.10.attention.self.key",
+    "encoder.layer.11.attention.self.key",
+    "encoder.layer.9.attention.self.query",
+    "encoder.layer.9.intermediate.dense",
+    "encoder.layer.10.attention.self.query",
+    "encoder.layer.10.attention.output.dense",
+    "encoder.layer.10.intermediate.dense",
+    "encoder.layer.11.attention.self.value",
+    "encoder.layer.11.attention.output.dense",
+    "encoder.layer.9.attention.self.value",
+    "encoder.layer.11.attention.self.query",
+    "encoder.layer.10.output.dense",
+    "encoder.layer.9.attention.self.key",
+    "encoder.layer.9.output.dense",
+    "encoder.layer.11.output.dense",
+    "encoder.layer.11.intermediate.dense"
+  ],
+  "target_parameters": null,
+  "task_type": null,
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

core-text-cls-jigsaw-toxicity/10k/fold_2/meta.json

@@ -0,0 +1,51 @@
+{
+  "dataset": "BIN_TEXT_JIGSAW_TOXICITY",
+  "encoder": "e5-small-tar",
+  "model": "intfloat/e5-small-v2",
+  "size": "10k",
+  "fold": 2,
+  "n_train": 10000,
+  "n_test": 5000,
+  "lora": {
+    "learning_rate": 0.0001,
+    "epochs": 50,
+    "lora_rank": 16,
+    "layers": 3,
+    "patience": 3,
+    "weight_decay": 0.001,
+    "batch_size": 256
+  },
+  "best_val_loss": 0.11818765103816986,
+  "epochs": 18.0,
+  "n_rows": 15000,
+  "n_inputs": 14992,
+  "n_columns": 31,
+  "features": [
+    "comment_text"
+  ],
+  "finetune_seconds": 256.04765517299984,
+  "encode_seconds": {
+    "comment_text": 9.176779805000024
+  },
+  "total_seconds": 265.22443497799986,
+  "git": "12b5c55",
+  "timestamp": "2026-10-18 08:50:47",
+  "gpu_type": "NVIDIA H100 80GB HBM3",
+  "gpu_total_memory_gb": 79.1787109375,
+  "use_gpu": true,
+  "cpu_cores": 8,
+  "system_ram_gb": 230.04119110107422,
+  "cpu_name": "Intel(R) Xeon(R) Platinum 8481C CPU @ 2.70GHz",
+  "visible_cpus": 8,
+  "ram_limit_gb": 32.0,
+  "expected_hardware": {
+    "gpu_prefix": "NVIDIA A100",
+    "cpu_prefix": null,
+    "cpus": 6,
+    "ram_gb": 32
+  },
+  "official_hardware_mismatches": [
+    "GPU is NVIDIA H100 80GB HBM3, not NVIDIA A100",
+    "8 CPUs are available, not 6"
+  ]
+}

core-text-cls-jigsaw-toxicity/10k/fold_3/README.md

@@ -0,0 +1,206 @@
+---
+base_model: intfloat/e5-small-v2
+library_name: peft
+tags:
+- base_model:adapter:intfloat/e5-small-v2
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **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]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### 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
+
+- PEFT 0.18.0

core-text-cls-jigsaw-toxicity/10k/fold_3/adapter_config.json

@@ -0,0 +1,60 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "BertModel",
+    "parent_library": "transformers.models.bert.modeling_bert"
+  },
+  "base_model_name_or_path": "intfloat/e5-small-v2",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "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": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "encoder.layer.10.attention.self.query",
+    "encoder.layer.10.attention.output.dense",
+    "encoder.layer.11.attention.self.key",
+    "encoder.layer.11.attention.self.value",
+    "encoder.layer.11.output.dense",
+    "encoder.layer.9.intermediate.dense",
+    "encoder.layer.9.attention.self.value",
+    "encoder.layer.9.attention.output.dense",
+    "encoder.layer.10.intermediate.dense",
+    "encoder.layer.10.output.dense",
+    "encoder.layer.11.attention.self.query",
+    "encoder.layer.11.attention.output.dense",
+    "encoder.layer.9.output.dense",
+    "encoder.layer.10.attention.self.key",
+    "encoder.layer.11.intermediate.dense",
+    "encoder.layer.9.attention.self.key",
+    "encoder.layer.9.attention.self.query",
+    "encoder.layer.10.attention.self.value"
+  ],
+  "target_parameters": null,
+  "task_type": null,
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

core-text-cls-jigsaw-toxicity/10k/fold_3/meta.json

@@ -0,0 +1,51 @@
+{
+  "dataset": "BIN_TEXT_JIGSAW_TOXICITY",
+  "encoder": "e5-small-tar",
+  "model": "intfloat/e5-small-v2",
+  "size": "10k",
+  "fold": 3,
+  "n_train": 10000,
+  "n_test": 5000,
+  "lora": {
+    "learning_rate": 0.0001,
+    "epochs": 50,
+    "lora_rank": 16,
+    "layers": 3,
+    "patience": 3,
+    "weight_decay": 0.001,
+    "batch_size": 256
+  },
+  "best_val_loss": 0.10837697237730026,
+  "epochs": 16.0,
+  "n_rows": 15000,
+  "n_inputs": 14982,
+  "n_columns": 31,
+  "features": [
+    "comment_text"
+  ],
+  "finetune_seconds": 227.81700828099974,
+  "encode_seconds": {
+    "comment_text": 9.053686779000145
+  },
+  "total_seconds": 236.8706950599999,
+  "git": "12b5c55",
+  "timestamp": "2026-10-18 08:54:58",
+  "gpu_type": "NVIDIA H100 80GB HBM3",
+  "gpu_total_memory_gb": 79.1787109375,
+  "use_gpu": true,
+  "cpu_cores": 8,
+  "system_ram_gb": 230.04119110107422,
+  "cpu_name": "Intel(R) Xeon(R) Platinum 8481C CPU @ 2.70GHz",
+  "visible_cpus": 8,
+  "ram_limit_gb": 32.0,
+  "expected_hardware": {
+    "gpu_prefix": "NVIDIA A100",
+    "cpu_prefix": null,
+    "cpus": 6,
+    "ram_gb": 32
+  },
+  "official_hardware_mismatches": [
+    "GPU is NVIDIA H100 80GB HBM3, not NVIDIA A100",
+    "8 CPUs are available, not 6"
+  ]
+}

core-text-cls-jigsaw-toxicity/10k/fold_4/README.md

@@ -0,0 +1,206 @@
+---
+base_model: intfloat/e5-small-v2
+library_name: peft
+tags:
+- base_model:adapter:intfloat/e5-small-v2
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **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]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### 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
+
+- PEFT 0.18.0

core-text-cls-jigsaw-toxicity/10k/fold_4/adapter_config.json

@@ -0,0 +1,60 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "BertModel",
+    "parent_library": "transformers.models.bert.modeling_bert"
+  },
+  "base_model_name_or_path": "intfloat/e5-small-v2",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "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": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "encoder.layer.10.attention.self.value",
+    "encoder.layer.10.output.dense",
+    "encoder.layer.11.attention.self.query",
+    "encoder.layer.11.output.dense",
+    "encoder.layer.9.attention.output.dense",
+    "encoder.layer.11.attention.self.key",
+    "encoder.layer.9.attention.self.key",
+    "encoder.layer.11.attention.output.dense",
+    "encoder.layer.9.intermediate.dense",
+    "encoder.layer.9.output.dense",
+    "encoder.layer.10.attention.self.query",
+    "encoder.layer.10.attention.self.key",
+    "encoder.layer.11.attention.self.value",
+    "encoder.layer.11.intermediate.dense",
+    "encoder.layer.9.attention.self.value",
+    "encoder.layer.10.intermediate.dense",
+    "encoder.layer.10.attention.output.dense",
+    "encoder.layer.9.attention.self.query"
+  ],
+  "target_parameters": null,
+  "task_type": null,
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

core-text-cls-jigsaw-toxicity/10k/fold_4/meta.json

@@ -0,0 +1,51 @@
+{
+  "dataset": "BIN_TEXT_JIGSAW_TOXICITY",
+  "encoder": "e5-small-tar",
+  "model": "intfloat/e5-small-v2",
+  "size": "10k",
+  "fold": 4,
+  "n_train": 10000,
+  "n_test": 5000,
+  "lora": {
+    "learning_rate": 0.0001,
+    "epochs": 50,
+    "lora_rank": 16,
+    "layers": 3,
+    "patience": 3,
+    "weight_decay": 0.001,
+    "batch_size": 256
+  },
+  "best_val_loss": 0.11817831546068192,
+  "epochs": 16.0,
+  "n_rows": 15000,
+  "n_inputs": 14989,
+  "n_columns": 31,
+  "features": [
+    "comment_text"
+  ],
+  "finetune_seconds": 227.88917803899994,
+  "encode_seconds": {
+    "comment_text": 9.104562911999892
+  },
+  "total_seconds": 236.99374095099984,
+  "git": "12b5c55",
+  "timestamp": "2026-10-18 08:59:10",
+  "gpu_type": "NVIDIA H100 80GB HBM3",
+  "gpu_total_memory_gb": 79.1787109375,
+  "use_gpu": true,
+  "cpu_cores": 8,
+  "system_ram_gb": 230.04119110107422,
+  "cpu_name": "Intel(R) Xeon(R) Platinum 8481C CPU @ 2.70GHz",
+  "visible_cpus": 8,
+  "ram_limit_gb": 32.0,
+  "expected_hardware": {
+    "gpu_prefix": "NVIDIA A100",
+    "cpu_prefix": null,
+    "cpus": 6,
+    "ram_gb": 32
+  },
+  "official_hardware_mismatches": [
+    "GPU is NVIDIA H100 80GB HBM3, not NVIDIA A100",
+    "8 CPUs are available, not 6"
+  ]
+}

core-text-cls-jigsaw-toxicity/10k/fold_5/README.md

@@ -0,0 +1,206 @@
+---
+base_model: intfloat/e5-small-v2
+library_name: peft
+tags:
+- base_model:adapter:intfloat/e5-small-v2
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **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]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### 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
+
+- PEFT 0.18.0

core-text-cls-jigsaw-toxicity/10k/fold_5/adapter_config.json

@@ -0,0 +1,60 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "BertModel",
+    "parent_library": "transformers.models.bert.modeling_bert"
+  },
+  "base_model_name_or_path": "intfloat/e5-small-v2",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "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": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "encoder.layer.10.attention.self.query",
+    "encoder.layer.9.attention.self.key",
+    "encoder.layer.11.attention.self.query",
+    "encoder.layer.11.intermediate.dense",
+    "encoder.layer.9.intermediate.dense",
+    "encoder.layer.11.attention.output.dense",
+    "encoder.layer.9.attention.output.dense",
+    "encoder.layer.9.output.dense",
+    "encoder.layer.9.attention.self.value",
+    "encoder.layer.10.output.dense",
+    "encoder.layer.11.attention.self.key",
+    "encoder.layer.10.attention.self.value",
+    "encoder.layer.10.attention.output.dense",
+    "encoder.layer.11.attention.self.value",
+    "encoder.layer.10.intermediate.dense",
+    "encoder.layer.11.output.dense",
+    "encoder.layer.10.attention.self.key",
+    "encoder.layer.9.attention.self.query"
+  ],
+  "target_parameters": null,
+  "task_type": null,
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

core-text-cls-jigsaw-toxicity/10k/fold_5/meta.json

@@ -0,0 +1,51 @@
+{
+  "dataset": "BIN_TEXT_JIGSAW_TOXICITY",
+  "encoder": "e5-small-tar",
+  "model": "intfloat/e5-small-v2",
+  "size": "10k",
+  "fold": 5,
+  "n_train": 10000,
+  "n_test": 5000,
+  "lora": {
+    "learning_rate": 0.0001,
+    "epochs": 50,
+    "lora_rank": 16,
+    "layers": 3,
+    "patience": 3,
+    "weight_decay": 0.001,
+    "batch_size": 256
+  },
+  "best_val_loss": 0.1350056231021881,
+  "epochs": 13.0,
+  "n_rows": 15000,
+  "n_inputs": 14989,
+  "n_columns": 31,
+  "features": [
+    "comment_text"
+  ],
+  "finetune_seconds": 184.9347590110001,
+  "encode_seconds": {
+    "comment_text": 9.13287537899987
+  },
+  "total_seconds": 194.06763438999997,
+  "git": "12b5c55",
+  "timestamp": "2026-10-18 09:02:38",
+  "gpu_type": "NVIDIA H100 80GB HBM3",
+  "gpu_total_memory_gb": 79.1787109375,
+  "use_gpu": true,
+  "cpu_cores": 8,
+  "system_ram_gb": 230.04119110107422,
+  "cpu_name": "Intel(R) Xeon(R) Platinum 8481C CPU @ 2.70GHz",
+  "visible_cpus": 8,
+  "ram_limit_gb": 32.0,
+  "expected_hardware": {
+    "gpu_prefix": "NVIDIA A100",
+    "cpu_prefix": null,
+    "cpus": 6,
+    "ram_gb": 32
+  },
+  "official_hardware_mismatches": [
+    "GPU is NVIDIA H100 80GB HBM3, not NVIDIA A100",
+    "8 CPUs are available, not 6"
+  ]
+}

core-text-cls-spotify-genres/10k/fold_0/README.md

@@ -0,0 +1,206 @@
+---
+base_model: intfloat/e5-small-v2
+library_name: peft
+tags:
+- base_model:adapter:intfloat/e5-small-v2
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **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]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### 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
+
+- PEFT 0.18.0

core-text-cls-spotify-genres/10k/fold_0/adapter_config.json

@@ -0,0 +1,60 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "BertModel",
+    "parent_library": "transformers.models.bert.modeling_bert"
+  },
+  "base_model_name_or_path": "intfloat/e5-small-v2",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "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": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "encoder.layer.11.attention.self.value",
+    "encoder.layer.11.attention.output.dense",
+    "encoder.layer.9.intermediate.dense",
+    "encoder.layer.10.attention.output.dense",
+    "encoder.layer.10.attention.self.value",
+    "encoder.layer.9.attention.self.query",
+    "encoder.layer.10.intermediate.dense",
+    "encoder.layer.11.intermediate.dense",
+    "encoder.layer.9.attention.output.dense",
+    "encoder.layer.10.output.dense",
+    "encoder.layer.10.attention.self.query",
+    "encoder.layer.11.output.dense",
+    "encoder.layer.9.output.dense",
+    "encoder.layer.9.attention.self.value",
+    "encoder.layer.9.attention.self.key",
+    "encoder.layer.11.attention.self.key",
+    "encoder.layer.11.attention.self.query",
+    "encoder.layer.10.attention.self.key"
+  ],
+  "target_parameters": null,
+  "task_type": null,
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

core-text-cls-spotify-genres/10k/fold_0/meta.json

@@ -0,0 +1,55 @@
+{
+  "dataset": "MUL_TEXT_SPOTIFY_GENRES",
+  "encoder": "e5-small-tar",
+  "model": "intfloat/e5-small-v2",
+  "size": "10k",
+  "fold": 0,
+  "n_train": 10000,
+  "n_test": 5000,
+  "lora": {
+    "learning_rate": 0.0001,
+    "epochs": 50,
+    "lora_rank": 16,
+    "layers": 3,
+    "patience": 3,
+    "weight_decay": 0.001,
+    "batch_size": 256
+  },
+  "best_val_loss": 3.6384694576263428,
+  "epochs": 50.0,
+  "n_rows": 15000,
+  "n_inputs": 32865,
+  "n_columns": 18,
+  "features": [
+    "album_name",
+    "artists",
+    "track_name"
+  ],
+  "finetune_seconds": 2041.0610729730006,
+  "encode_seconds": {
+    "album_name": 2.4566243509998458,
+    "artists": 1.9671957470000052,
+    "track_name": 3.0257431090003593
+  },
+  "total_seconds": 2048.510636180001,
+  "git": "12b5c55",
+  "timestamp": "2026-10-18 10:43:57",
+  "gpu_type": "NVIDIA H100 80GB HBM3",
+  "gpu_total_memory_gb": 79.1787109375,
+  "use_gpu": true,
+  "cpu_cores": 8,
+  "system_ram_gb": 230.04119873046875,
+  "cpu_name": "Intel(R) Xeon(R) Platinum 8481C CPU @ 2.70GHz",
+  "visible_cpus": 8,
+  "ram_limit_gb": 32.0,
+  "expected_hardware": {
+    "gpu_prefix": "NVIDIA A100",
+    "cpu_prefix": null,
+    "cpus": 6,
+    "ram_gb": 32
+  },
+  "official_hardware_mismatches": [
+    "GPU is NVIDIA H100 80GB HBM3, not NVIDIA A100",
+    "8 CPUs are available, not 6"
+  ]
+}

core-text-cls-spotify-genres/10k/fold_1/README.md

@@ -0,0 +1,206 @@
+---
+base_model: intfloat/e5-small-v2
+library_name: peft
+tags:
+- base_model:adapter:intfloat/e5-small-v2
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **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]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### 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
+
+- PEFT 0.18.0

core-text-cls-spotify-genres/10k/fold_1/adapter_config.json

@@ -0,0 +1,60 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "BertModel",
+    "parent_library": "transformers.models.bert.modeling_bert"
+  },
+  "base_model_name_or_path": "intfloat/e5-small-v2",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "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": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "encoder.layer.10.attention.self.query",
+    "encoder.layer.9.attention.self.query",
+    "encoder.layer.10.output.dense",
+    "encoder.layer.11.output.dense",
+    "encoder.layer.10.intermediate.dense",
+    "encoder.layer.9.output.dense",
+    "encoder.layer.9.attention.output.dense",
+    "encoder.layer.10.attention.self.key",
+    "encoder.layer.9.attention.self.value",
+    "encoder.layer.11.intermediate.dense",
+    "encoder.layer.9.attention.self.key",
+    "encoder.layer.11.attention.self.value",
+    "encoder.layer.10.attention.self.value",
+    "encoder.layer.9.intermediate.dense",
+    "encoder.layer.11.attention.output.dense",
+    "encoder.layer.11.attention.self.key",
+    "encoder.layer.10.attention.output.dense",
+    "encoder.layer.11.attention.self.query"
+  ],
+  "target_parameters": null,
+  "task_type": null,
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

core-text-cls-spotify-genres/10k/fold_1/meta.json

@@ -0,0 +1,55 @@
+{
+  "dataset": "MUL_TEXT_SPOTIFY_GENRES",
+  "encoder": "e5-small-tar",
+  "model": "intfloat/e5-small-v2",
+  "size": "10k",
+  "fold": 1,
+  "n_train": 10000,
+  "n_test": 5000,
+  "lora": {
+    "learning_rate": 0.0001,
+    "epochs": 50,
+    "lora_rank": 16,
+    "layers": 3,
+    "patience": 3,
+    "weight_decay": 0.001,
+    "batch_size": 256
+  },
+  "best_val_loss": 3.672360897064209,
+  "epochs": 50.0,
+  "n_rows": 15000,
+  "n_inputs": 32702,
+  "n_columns": 18,
+  "features": [
+    "album_name",
+    "artists",
+    "track_name"
+  ],
+  "finetune_seconds": 2041.1433059500005,
+  "encode_seconds": {
+    "album_name": 2.4256007139993017,
+    "artists": 1.9547137520003162,
+    "track_name": 2.963067697999577
+  },
+  "total_seconds": 2048.4866881139997,
+  "git": "12b5c55",
+  "timestamp": "2026-10-18 11:18:20",
+  "gpu_type": "NVIDIA H100 80GB HBM3",
+  "gpu_total_memory_gb": 79.1787109375,
+  "use_gpu": true,
+  "cpu_cores": 8,
+  "system_ram_gb": 230.04119873046875,
+  "cpu_name": "Intel(R) Xeon(R) Platinum 8481C CPU @ 2.70GHz",
+  "visible_cpus": 8,
+  "ram_limit_gb": 32.0,
+  "expected_hardware": {
+    "gpu_prefix": "NVIDIA A100",
+    "cpu_prefix": null,
+    "cpus": 6,
+    "ram_gb": 32
+  },
+  "official_hardware_mismatches": [
+    "GPU is NVIDIA H100 80GB HBM3, not NVIDIA A100",
+    "8 CPUs are available, not 6"
+  ]
+}

core-text-cls-spotify-genres/10k/fold_2/README.md

@@ -0,0 +1,206 @@
+---
+base_model: intfloat/e5-small-v2
+library_name: peft
+tags:
+- base_model:adapter:intfloat/e5-small-v2
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **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]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### 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
+
+- PEFT 0.18.0

core-text-cls-spotify-genres/10k/fold_2/adapter_config.json

@@ -0,0 +1,60 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "BertModel",
+    "parent_library": "transformers.models.bert.modeling_bert"
+  },
+  "base_model_name_or_path": "intfloat/e5-small-v2",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "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": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "encoder.layer.10.attention.output.dense",
+    "encoder.layer.11.intermediate.dense",
+    "encoder.layer.9.attention.self.value",
+    "encoder.layer.10.intermediate.dense",
+    "encoder.layer.9.attention.self.query",
+    "encoder.layer.9.attention.self.key",
+    "encoder.layer.9.output.dense",
+    "encoder.layer.11.attention.self.value",
+    "encoder.layer.10.attention.self.query",
+    "encoder.layer.9.attention.output.dense",
+    "encoder.layer.10.output.dense",
+    "encoder.layer.9.intermediate.dense",
+    "encoder.layer.11.output.dense",
+    "encoder.layer.11.attention.self.query",
+    "encoder.layer.10.attention.self.value",
+    "encoder.layer.11.attention.self.key",
+    "encoder.layer.11.attention.output.dense",
+    "encoder.layer.10.attention.self.key"
+  ],
+  "target_parameters": null,
+  "task_type": null,
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

core-text-cls-spotify-genres/10k/fold_2/meta.json

@@ -0,0 +1,55 @@
+{
+  "dataset": "MUL_TEXT_SPOTIFY_GENRES",
+  "encoder": "e5-small-tar",
+  "model": "intfloat/e5-small-v2",
+  "size": "10k",
+  "fold": 2,
+  "n_train": 10000,
+  "n_test": 5000,
+  "lora": {
+    "learning_rate": 0.0001,
+    "epochs": 50,
+    "lora_rank": 16,
+    "layers": 3,
+    "patience": 3,
+    "weight_decay": 0.001,
+    "batch_size": 256
+  },
+  "best_val_loss": 3.653848886489868,
+  "epochs": 45.0,
+  "n_rows": 15000,
+  "n_inputs": 32934,
+  "n_columns": 18,
+  "features": [
+    "album_name",
+    "artists",
+    "track_name"
+  ],
+  "finetune_seconds": 1837.255926621001,
+  "encode_seconds": {
+    "album_name": 2.438699689000714,
+    "artists": 2.005515582000953,
+    "track_name": 2.9774902110002586
+  },
+  "total_seconds": 1844.677632103003,
+  "git": "12b5c55",
+  "timestamp": "2026-10-18 11:49:20",
+  "gpu_type": "NVIDIA H100 80GB HBM3",
+  "gpu_total_memory_gb": 79.1787109375,
+  "use_gpu": true,
+  "cpu_cores": 8,
+  "system_ram_gb": 230.04119873046875,
+  "cpu_name": "Intel(R) Xeon(R) Platinum 8481C CPU @ 2.70GHz",
+  "visible_cpus": 8,
+  "ram_limit_gb": 32.0,
+  "expected_hardware": {
+    "gpu_prefix": "NVIDIA A100",
+    "cpu_prefix": null,
+    "cpus": 6,
+    "ram_gb": 32
+  },
+  "official_hardware_mismatches": [
+    "GPU is NVIDIA H100 80GB HBM3, not NVIDIA A100",
+    "8 CPUs are available, not 6"
+  ]
+}

core-text-cls-spotify-genres/10k/fold_3/README.md

@@ -0,0 +1,206 @@
+---
+base_model: intfloat/e5-small-v2
+library_name: peft
+tags:
+- base_model:adapter:intfloat/e5-small-v2
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **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]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### 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
+
+- PEFT 0.18.0

core-text-cls-spotify-genres/10k/fold_3/adapter_config.json

@@ -0,0 +1,60 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "BertModel",
+    "parent_library": "transformers.models.bert.modeling_bert"
+  },
+  "base_model_name_or_path": "intfloat/e5-small-v2",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "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": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "encoder.layer.11.attention.self.key",
+    "encoder.layer.11.intermediate.dense",
+    "encoder.layer.9.output.dense",
+    "encoder.layer.11.attention.self.value",
+    "encoder.layer.10.attention.self.value",
+    "encoder.layer.11.attention.output.dense",
+    "encoder.layer.10.intermediate.dense",
+    "encoder.layer.9.attention.self.query",
+    "encoder.layer.10.output.dense",
+    "encoder.layer.11.output.dense",
+    "encoder.layer.9.attention.output.dense",
+    "encoder.layer.10.attention.self.query",
+    "encoder.layer.9.attention.self.value",
+    "encoder.layer.10.attention.self.key",
+    "encoder.layer.11.attention.self.query",
+    "encoder.layer.9.intermediate.dense",
+    "encoder.layer.9.attention.self.key",
+    "encoder.layer.10.attention.output.dense"
+  ],
+  "target_parameters": null,
+  "task_type": null,
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

core-text-cls-spotify-genres/10k/fold_3/meta.json

@@ -0,0 +1,55 @@
+{
+  "dataset": "MUL_TEXT_SPOTIFY_GENRES",
+  "encoder": "e5-small-tar",
+  "model": "intfloat/e5-small-v2",
+  "size": "10k",
+  "fold": 3,
+  "n_train": 10000,
+  "n_test": 5000,
+  "lora": {
+    "learning_rate": 0.0001,
+    "epochs": 50,
+    "lora_rank": 16,
+    "layers": 3,
+    "patience": 3,
+    "weight_decay": 0.001,
+    "batch_size": 256
+  },
+  "best_val_loss": 3.601576089859009,
+  "epochs": 50.0,
+  "n_rows": 15000,
+  "n_inputs": 32658,
+  "n_columns": 18,
+  "features": [
+    "album_name",
+    "artists",
+    "track_name"
+  ],
+  "finetune_seconds": 2041.3078559779988,
+  "encode_seconds": {
+    "album_name": 2.4263571809988207,
+    "artists": 1.992828386999463,
+    "track_name": 2.951474859000882
+  },
+  "total_seconds": 2048.678516404998,
+  "git": "12b5c55",
+  "timestamp": "2026-10-18 12:23:44",
+  "gpu_type": "NVIDIA H100 80GB HBM3",
+  "gpu_total_memory_gb": 79.1787109375,
+  "use_gpu": true,
+  "cpu_cores": 8,
+  "system_ram_gb": 230.04119873046875,
+  "cpu_name": "Intel(R) Xeon(R) Platinum 8481C CPU @ 2.70GHz",
+  "visible_cpus": 8,
+  "ram_limit_gb": 32.0,
+  "expected_hardware": {
+    "gpu_prefix": "NVIDIA A100",
+    "cpu_prefix": null,
+    "cpus": 6,
+    "ram_gb": 32
+  },
+  "official_hardware_mismatches": [
+    "GPU is NVIDIA H100 80GB HBM3, not NVIDIA A100",
+    "8 CPUs are available, not 6"
+  ]
+}

core-text-cls-spotify-genres/10k/fold_4/README.md

@@ -0,0 +1,206 @@
+---
+base_model: intfloat/e5-small-v2
+library_name: peft
+tags:
+- base_model:adapter:intfloat/e5-small-v2
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **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]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### 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
+
+- PEFT 0.18.0

core-text-cls-spotify-genres/10k/fold_4/adapter_config.json

@@ -0,0 +1,60 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "BertModel",
+    "parent_library": "transformers.models.bert.modeling_bert"
+  },
+  "base_model_name_or_path": "intfloat/e5-small-v2",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "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": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "encoder.layer.11.attention.self.value",
+    "encoder.layer.10.attention.self.query",
+    "encoder.layer.9.output.dense",
+    "encoder.layer.9.attention.self.value",
+    "encoder.layer.10.output.dense",
+    "encoder.layer.9.attention.self.query",
+    "encoder.layer.10.attention.self.key",
+    "encoder.layer.11.attention.self.query",
+    "encoder.layer.11.attention.self.key",
+    "encoder.layer.11.attention.output.dense",
+    "encoder.layer.11.intermediate.dense",
+    "encoder.layer.10.attention.output.dense",
+    "encoder.layer.10.attention.self.value",
+    "encoder.layer.11.output.dense",
+    "encoder.layer.9.attention.self.key",
+    "encoder.layer.9.attention.output.dense",
+    "encoder.layer.10.intermediate.dense",
+    "encoder.layer.9.intermediate.dense"
+  ],
+  "target_parameters": null,
+  "task_type": null,
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}